%% $Id$

\chapter{The Classical Reasoner}\label{chap:classical}

\index{classical reasoner|(}

\newcommand\ainfer[2]{\begin{array}{r@{\,}l}#2\\ \hline#1\end{array}}

Although Isabelle is generic, many users will be working in some

extension of classical first-order logic.  Isabelle's set theory~{\tt

  ZF} is built upon theory~\texttt{FOL}, while {\HOL}

conceptually contains first-order logic as a fragment.

Theorem-proving in predicate logic is undecidable, but many

researchers have developed strategies to assist in this task.

Isabelle's classical reasoner is an \ML{} functor that accepts certain

information about a logic and delivers a suite of automatic tactics.  Each

tactic takes a collection of rules and executes a simple, non-clausal proof

procedure.  They are slow and simplistic compared with resolution theorem

provers, but they can save considerable time and effort.  They can prove

theorems such as Pelletier's~\cite{pelletier86} problems~40 and~41 in

seconds:

\[ (\exists y. \forall x. J(y,x) \bimp \neg J(x,x))  

   \imp  \neg (\forall x. \exists y. \forall z. J(z,y) \bimp \neg J(z,x)) \]

\[ (\forall z. \exists y. \forall x. F(x,y) \bimp F(x,z) \conj \neg F(x,x))

   \imp \neg (\exists z. \forall x. F(x,z))  

\]

%

The tactics are generic.  They are not restricted to first-order logic, and

have been heavily used in the development of Isabelle's set theory.  Few

interactive proof assistants provide this much automation.  The tactics can

be traced, and their components can be called directly; in this manner,

any proof can be viewed interactively.

The simplest way to apply the classical reasoner (to subgoal~$i$) is to type

\begin{ttbox}

by (Blast_tac \(i\));

\end{ttbox}

This command quickly proves most simple formulas of the predicate calculus or

set theory.  To attempt to prove \emph{all} subgoals using a combination of

rewriting and classical reasoning, try

\begin{ttbox}

by Auto_tac;

\end{ttbox}

To do all obvious logical steps, even if they do not prove the

subgoal, type one of the following:

\begin{ttbox}

by (Clarify_tac \(i\));        \emph{\textrm{applies to one subgoal}}

by Safe_tac;               \emph{\textrm{applies to all subgoals}}

\end{ttbox}

You need to know how the classical reasoner works in order to use it

effectively.  There are many tactics to choose from, including {\tt

  Fast_tac} and \texttt{Best_tac}.

We shall first discuss the underlying principles, then present the

classical reasoner.  Finally, we shall see how to instantiate it for

new logics.  The logics \FOL, \ZF, {\HOL} and {\HOLCF} have it already

installed.

\section{The sequent calculus}

\index{sequent calculus}

Isabelle supports natural deduction, which is easy to use for interactive

proof.  But natural deduction does not easily lend itself to automation,

and has a bias towards intuitionism.  For certain proofs in classical

logic, it can not be called natural.  The {\bf sequent calculus}, a

generalization of natural deduction, is easier to automate.

A {\bf sequent} has the form $\Gamma\turn\Delta$, where $\Gamma$

and~$\Delta$ are sets of formulae.%

\footnote{For first-order logic, sequents can equivalently be made from

  lists or multisets of formulae.} The sequent

\[ P@1,\ldots,P@m\turn Q@1,\ldots,Q@n \]

is {\bf valid} if $P@1\conj\ldots\conj P@m$ implies $Q@1\disj\ldots\disj

Q@n$.  Thus $P@1,\ldots,P@m$ represent assumptions, each of which is true,

while $Q@1,\ldots,Q@n$ represent alternative goals.  A sequent is {\bf

basic} if its left and right sides have a common formula, as in $P,Q\turn

Q,R$; basic sequents are trivially valid.

Sequent rules are classified as {\bf right} or {\bf left}, indicating which

side of the $\turn$~symbol they operate on.  Rules that operate on the

right side are analogous to natural deduction's introduction rules, and

left rules are analogous to elimination rules.  

Recall the natural deduction rules for

  first-order logic, 

\iflabelundefined{fol-fig}{from {\it Introduction to Isabelle}}%

                          {Fig.\ts\ref{fol-fig}}.

The sequent calculus analogue of~$({\imp}I)$ is the rule

$$

\ainfer{\Gamma &\turn \Delta, P\imp Q}{P,\Gamma &\turn \Delta,Q}

\eqno({\imp}R)

$$

This breaks down some implication on the right side of a sequent; $\Gamma$

and $\Delta$ stand for the sets of formulae that are unaffected by the

inference.  The analogue of the pair~$({\disj}I1)$ and~$({\disj}I2)$ is the

single rule 

$$

\ainfer{\Gamma &\turn \Delta, P\disj Q}{\Gamma &\turn \Delta,P,Q}

\eqno({\disj}R)

$$

This breaks down some disjunction on the right side, replacing it by both

disjuncts.  Thus, the sequent calculus is a kind of multiple-conclusion logic.

To illustrate the use of multiple formulae on the right, let us prove

the classical theorem $(P\imp Q)\disj(Q\imp P)$.  Working backwards, we

reduce this formula to a basic sequent:

\[ \infer[(\disj)R]{\turn(P\imp Q)\disj(Q\imp P)}

   {\infer[(\imp)R]{\turn(P\imp Q), (Q\imp P)\;}

    {\infer[(\imp)R]{P \turn Q, (Q\imp P)\qquad}

                    {P, Q \turn Q, P\qquad\qquad}}}

\]

This example is typical of the sequent calculus: start with the desired

theorem and apply rules backwards in a fairly arbitrary manner.  This yields a

surprisingly effective proof procedure.  Quantifiers add few complications,

since Isabelle handles parameters and schematic variables.  See Chapter~10

of {\em ML for the Working Programmer}~\cite{paulson91} for further

discussion.

\section{Simulating sequents by natural deduction}

Isabelle can represent sequents directly, as in the object-logic~\texttt{LK}\@.

But natural deduction is easier to work with, and most object-logics employ

it.  Fortunately, we can simulate the sequent $P@1,\ldots,P@m\turn

Q@1,\ldots,Q@n$ by the Isabelle formula

\[ \List{P@1;\ldots;P@m; \neg Q@2;\ldots; \neg Q@n}\Imp Q@1, \]

where the order of the assumptions and the choice of~$Q@1$ are arbitrary.

Elim-resolution plays a key role in simulating sequent proofs.

We can easily handle reasoning on the left.

As discussed in

\iflabelundefined{destruct}{{\it Introduction to Isabelle}}{\S\ref{destruct}}, 

elim-resolution with the rules $(\disj E)$, $(\bot E)$ and $(\exists E)$

achieves a similar effect as the corresponding sequent rules.  For the

other connectives, we use sequent-style elimination rules instead of

destruction rules such as $({\conj}E1,2)$ and $(\forall E)$.  But note that

the rule $(\neg L)$ has no effect under our representation of sequents!

$$

\ainfer{\neg P,\Gamma &\turn \Delta}{\Gamma &\turn \Delta,P}\eqno({\neg}L)

$$

What about reasoning on the right?  Introduction rules can only affect the

formula in the conclusion, namely~$Q@1$.  The other right-side formulae are

represented as negated assumptions, $\neg Q@2$, \ldots,~$\neg Q@n$.  

\index{assumptions!negated}

In order to operate on one of these, it must first be exchanged with~$Q@1$.

Elim-resolution with the {\bf swap} rule has this effect:

$$ \List{\neg P; \; \neg R\Imp P} \Imp R   \eqno(swap)  $$

To ensure that swaps occur only when necessary, each introduction rule is

converted into a swapped form: it is resolved with the second premise

of~$(swap)$.  The swapped form of~$({\conj}I)$, which might be

called~$({\neg\conj}E)$, is

\[ \List{\neg(P\conj Q); \; \neg R\Imp P; \; \neg R\Imp Q} \Imp R. \]

Similarly, the swapped form of~$({\imp}I)$ is

\[ \List{\neg(P\imp Q); \; \List{\neg R;P}\Imp Q} \Imp R  \]

Swapped introduction rules are applied using elim-resolution, which deletes

the negated formula.  Our representation of sequents also requires the use

of ordinary introduction rules.  If we had no regard for readability, we

could treat the right side more uniformly by representing sequents as

\[ \List{P@1;\ldots;P@m; \neg Q@1;\ldots; \neg Q@n}\Imp \bot. \]

\section{Extra rules for the sequent calculus}

As mentioned, destruction rules such as $({\conj}E1,2)$ and $(\forall E)$

must be replaced by sequent-style elimination rules.  In addition, we need

rules to embody the classical equivalence between $P\imp Q$ and $\neg P\disj

Q$.  The introduction rules~$({\disj}I1,2)$ are replaced by a rule that

simulates $({\disj}R)$:

\[ (\neg Q\Imp P) \Imp P\disj Q \]

The destruction rule $({\imp}E)$ is replaced by

\[ \List{P\imp Q;\; \neg P\Imp R;\; Q\Imp R} \Imp R. \]

Quantifier replication also requires special rules.  In classical logic,

$\exists x{.}P$ is equivalent to $\neg\forall x{.}\neg P$; the rules

$(\exists R)$ and $(\forall L)$ are dual:

\[ \ainfer{\Gamma &\turn \Delta, \exists x{.}P}

          {\Gamma &\turn \Delta, \exists x{.}P, P[t/x]} \; (\exists R)

   \qquad

   \ainfer{\forall x{.}P, \Gamma &\turn \Delta}

          {P[t/x], \forall x{.}P, \Gamma &\turn \Delta} \; (\forall L)

\]

Thus both kinds of quantifier may be replicated.  Theorems requiring

multiple uses of a universal formula are easy to invent; consider 

\[ (\forall x.P(x)\imp P(f(x))) \conj P(a) \imp P(f^n(a)), \]

for any~$n>1$.  Natural examples of the multiple use of an existential

formula are rare; a standard one is $\exists x.\forall y. P(x)\imp P(y)$.

Forgoing quantifier replication loses completeness, but gains decidability,

since the search space becomes finite.  Many useful theorems can be proved

without replication, and the search generally delivers its verdict in a

reasonable time.  To adopt this approach, represent the sequent rules

$(\exists R)$, $(\exists L)$ and $(\forall R)$ by $(\exists I)$, $(\exists

E)$ and $(\forall I)$, respectively, and put $(\forall E)$ into elimination

form:

$$ \List{\forall x{.}P(x); P(t)\Imp Q} \Imp Q    \eqno(\forall E@2) $$

Elim-resolution with this rule will delete the universal formula after a

single use.  To replicate universal quantifiers, replace the rule by

$$

\List{\forall x{.}P(x);\; \List{P(t); \forall x{.}P(x)}\Imp Q} \Imp Q.

\eqno(\forall E@3)

$$

To replicate existential quantifiers, replace $(\exists I)$ by

\[ \List{\neg(\exists x{.}P(x)) \Imp P(t)} \Imp \exists x{.}P(x). \]

All introduction rules mentioned above are also useful in swapped form.

Replication makes the search space infinite; we must apply the rules with

care.  The classical reasoner distinguishes between safe and unsafe

rules, applying the latter only when there is no alternative.  Depth-first

search may well go down a blind alley; best-first search is better behaved

in an infinite search space.  However, quantifier replication is too

expensive to prove any but the simplest theorems.

\section{Classical rule sets}

\index{classical sets}

Each automatic tactic takes a {\bf classical set} --- a collection of

rules, classified as introduction or elimination and as {\bf safe} or {\bf

unsafe}.  In general, safe rules can be attempted blindly, while unsafe

rules must be used with care.  A safe rule must never reduce a provable

goal to an unprovable set of subgoals.  

The rule~$({\disj}I1)$ is unsafe because it reduces $P\disj Q$ to~$P$.  Any

rule is unsafe whose premises contain new unknowns.  The elimination

rule~$(\forall E@2)$ is unsafe, since it is applied via elim-resolution,

which discards the assumption $\forall x{.}P(x)$ and replaces it by the

weaker assumption~$P(\Var{t})$.  The rule $({\exists}I)$ is unsafe for

similar reasons.  The rule~$(\forall E@3)$ is unsafe in a different sense:

since it keeps the assumption $\forall x{.}P(x)$, it is prone to looping.

In classical first-order logic, all rules are safe except those mentioned

above.

The safe/unsafe distinction is vague, and may be regarded merely as a way

of giving some rules priority over others.  One could argue that

$({\disj}E)$ is unsafe, because repeated application of it could generate

exponentially many subgoals.  Induction rules are unsafe because inductive

proofs are difficult to set up automatically.  Any inference is unsafe that

instantiates an unknown in the proof state --- thus \ttindex{match_tac}

must be used, rather than \ttindex{resolve_tac}.  Even proof by assumption

is unsafe if it instantiates unknowns shared with other subgoals --- thus

\ttindex{eq_assume_tac} must be used, rather than \ttindex{assume_tac}.

\subsection{Adding rules to classical sets}

Classical rule sets belong to the abstract type \mltydx{claset}, which

supports the following operations (provided the classical reasoner is

installed!):

\begin{ttbox} 

empty_cs    : claset

print_cs    : claset -> unit

rep_cs      : claset -> {safeEs: thm list, safeIs: thm list,

                         hazEs: thm list,  hazIs: thm list, 

                         swrappers: (string * wrapper) list, 

                         uwrappers: (string * wrapper) list,

                         safe0_netpair: netpair, safep_netpair: netpair,

                           haz_netpair: netpair,   dup_netpair: netpair}

addSIs      : claset * thm list -> claset                 \hfill{\bf infix 4}

addSEs      : claset * thm list -> claset                 \hfill{\bf infix 4}

addSDs      : claset * thm list -> claset                 \hfill{\bf infix 4}

addIs       : claset * thm list -> claset                 \hfill{\bf infix 4}

addEs       : claset * thm list -> claset                 \hfill{\bf infix 4}

addDs       : claset * thm list -> claset                 \hfill{\bf infix 4}

delrules    : claset * thm list -> claset                 \hfill{\bf infix 4}

\end{ttbox}

The add operations ignore any rule already present in the claset with the same

classification (such as Safe Introduction).  They print a warning if the rule

has already been added with some other classification, but add the rule

anyway.  Calling \texttt{delrules} deletes all occurrences of a rule from the

claset, but see the warning below concerning destruction rules.

\begin{ttdescription}

\item[\ttindexbold{empty_cs}] is the empty classical set.

\item[\ttindexbold{print_cs} $cs$] displays the printable contents of~$cs$,

  which is the rules. All other parts are non-printable.

\item[\ttindexbold{rep_cs} $cs$] decomposes $cs$ as a record of its internal 

  components, namely the safe introduction and elimination rules, the unsafe

  introduction and elimination rules, the lists of safe and unsafe wrappers

  (see \ref{sec:modifying-search}), and the internalized forms of the rules.

\item[$cs$ addSIs $rules$] \indexbold{*addSIs}

adds safe introduction~$rules$ to~$cs$.

\item[$cs$ addSEs $rules$] \indexbold{*addSEs}

adds safe elimination~$rules$ to~$cs$.

\item[$cs$ addSDs $rules$] \indexbold{*addSDs}

adds safe destruction~$rules$ to~$cs$.

\item[$cs$ addIs $rules$] \indexbold{*addIs}

adds unsafe introduction~$rules$ to~$cs$.

\item[$cs$ addEs $rules$] \indexbold{*addEs}

adds unsafe elimination~$rules$ to~$cs$.

\item[$cs$ addDs $rules$] \indexbold{*addDs}

adds unsafe destruction~$rules$ to~$cs$.

\item[$cs$ delrules $rules$] \indexbold{*delrules}

deletes~$rules$ from~$cs$.  It prints a warning for those rules that are not

in~$cs$.

\end{ttdescription}

\begin{warn}

  If you added $rule$ using \texttt{addSDs} or \texttt{addDs}, then you must delete

  it as follows:

\begin{ttbox}

\(cs\) delrules [make_elim \(rule\)]

\end{ttbox}

\par\noindent

This is necessary because the operators \texttt{addSDs} and \texttt{addDs} convert

the destruction rules to elimination rules by applying \ttindex{make_elim},

and then insert them using \texttt{addSEs} and \texttt{addEs}, respectively.

\end{warn}

Introduction rules are those that can be applied using ordinary resolution.

The classical set automatically generates their swapped forms, which will

be applied using elim-resolution.  Elimination rules are applied using

elim-resolution.  In a classical set, rules are sorted by the number of new

subgoals they will yield; rules that generate the fewest subgoals will be

tried first (see \S\ref{biresolve_tac}).

\subsection{Modifying the search step}

\label{sec:modifying-search}

For a given classical set, the proof strategy is simple.  Perform as many safe

inferences as possible; or else, apply certain safe rules, allowing

instantiation of unknowns; or else, apply an unsafe rule.  The tactics also

eliminate assumptions of the form $x=t$ by substitution if they have been set

up to do so (see \texttt{hyp_subst_tacs} in~\S\ref{sec:classical-setup} below).

They may perform a form of Modus Ponens: if there are assumptions $P\imp Q$

and~$P$, then replace $P\imp Q$ by~$Q$.

The classical reasoning tactics --- except \texttt{blast_tac}! --- allow

you to modify this basic proof strategy by applying two lists of arbitrary 

{\bf wrapper tacticals} to it. 

The first wrapper list, which is considered to contain safe wrappers only, 

affects \ttindex{safe_step_tac} and all the tactics that call it.  

The second one, which may contain unsafe wrappers, affects \ttindex{step_tac}, 

\ttindex{slow_step_tac}, and the tactics that call them.

A wrapper transforms each step of the search, for example 

by invoking other tactics before or alternatively to the original step tactic. 

All members of a wrapper list are applied in turn to the respective step tactic.

Initially the two wrapper lists are empty, which means no modification of the

step tactics. Safe and unsafe wrappers are added to a claset 

with the functions given below, supplying them with wrapper names. 

These names may be used to selectively delete wrappers.

\begin{ttbox} 

type wrapper = (int -> tactic) -> (int -> tactic);

addSWrapper  : claset * (string *  wrapper       ) -> claset \hfill{\bf infix 4}

addSbefore   : claset * (string * (int -> tactic)) -> claset \hfill{\bf infix 4}

addSaltern   : claset * (string * (int -> tactic)) -> claset \hfill{\bf infix 4}

delSWrapper  : claset *  string                    -> claset \hfill{\bf infix 4}

addWrapper   : claset * (string *  wrapper       ) -> claset \hfill{\bf infix 4}

addbefore    : claset * (string * (int -> tactic)) -> claset \hfill{\bf infix 4}

addaltern    : claset * (string * (int -> tactic)) -> claset \hfill{\bf infix 4}

delWrapper   : claset *  string                    -> claset \hfill{\bf infix 4}

addSss       : claset * simpset -> claset                 \hfill{\bf infix 4}

addss        : claset * simpset -> claset                 \hfill{\bf infix 4}

\end{ttbox}

%

\begin{ttdescription}

\item[$cs$ addSWrapper $(name,wrapper)$] \indexbold{*addSWrapper}

adds a new wrapper, which should yield a safe tactic, 

to modify the existing safe step tactic.

\item[$cs$ addSbefore $(name,tac)$] \indexbold{*addSbefore}

adds the given tactic as safe wrapper, such that it is

applied {\em before} each safe step of the search.

\item[$cs$ addSaltern $(name,tac)$] \indexbold{*addSaltern}

adds the given tactic as safe wrapper, such that it is

applied when a safe step of the search would fail.

\item[$cs$ delSWrapper $name$] \indexbold{*delSWrapper}

deletes the safe wrapper with the given name.

\item[$cs$ addWrapper $(name,wrapper)$] \indexbold{*addWrapper}

adds a new wrapper to modify the existing (unsafe) step tactic.

\item[$cs$ addbefore $(name,tac)$] \indexbold{*addbefore}

adds the given tactic as unsafe wrapper, such that it is

applied {\em before} each step of the search.

\item[$cs$ addaltern $(name,tac)$] \indexbold{*addaltern}

adds the given tactic as unsafe wrapper, such that it is

applied when a step of the search would fail.

\item[$cs$ delWrapper $name$] \indexbold{*delWrapper}

deletes the unsafe wrapper with the given name.

\item[$cs$ addSss $ss$] \indexbold{*addss}

adds the simpset~$ss$ to the classical set.  The assumptions and goal will be

simplified, in a rather safe way, after each safe step of the search.

\item[$cs$ addss $ss$] \indexbold{*addss}

adds the simpset~$ss$ to the classical set.  The assumptions and goal will be

simplified, before the each unsafe step of the search.

\end{ttdescription}

\index{simplification!from classical reasoner} The wrapper tacticals

underly the operators addss and addSss, which are used as primitives 

for the automatic tactics described in \S\ref{sec:automatic-tactics}.

Strictly speaking, both operators are not part of the classical reasoner. 

They should be defined when the simplifier is installed:

\begin{ttbox}

infix 4 addSss addss;

fun  cs addSss ss = cs addSaltern ("safe_asm_full_simp_tac",

                         CHANGED o (safe_asm_full_simp_tac ss));

fun  cs addss  ss = cs addbefore  ("asm_full_simp_tac", 

                                    asm_full_simp_tac ss);

\end{ttbox}

\begin{warn}

Being defined as wrappers, these operators are inappropriate for adding more 

than one simpset at a time: the simpset added last overwrites any earlier ones.

When a simpset combined with a claset is to be augmented, this should done 

{\em before} combining it with the claset.

\end{warn}

\section{The classical tactics}

\index{classical reasoner!tactics} If installed, the classical module provides

powerful theorem-proving tactics.  Most of them have capitalized analogues

that use the default claset; see \S\ref{sec:current-claset}.

\subsection{Semi-automatic tactics}

\begin{ttbox} 

clarify_tac      : claset -> int -> tactic

clarify_step_tac : claset -> int -> tactic

\end{ttbox}

Use these when the automatic tactics fail.  They perform all the obvious

logical inferences that do not split the subgoal.  The result is a

simpler subgoal that can be tackled by other means, such as by

instantiating quantifiers yourself.

\begin{ttdescription}

\item[\ttindexbold{clarify_tac} $cs$ $i$] performs a series of safe steps on

subgoal~$i$ by repeatedly calling \texttt{clarify_step_tac}.

\item[\ttindexbold{clarify_step_tac} $cs$ $i$] performs a safe step on

  subgoal~$i$.  No splitting step is applied; for example, the subgoal $A\conj

  B$ is left as a conjunction.  Proof by assumption, Modus Ponens, etc., may be

  performed provided they do not instantiate unknowns.  Assumptions of the

  form $x=t$ may be eliminated.  The user-supplied safe wrapper tactical is

  applied.

\end{ttdescription}

\subsection{The tableau prover}

The tactic \texttt{blast_tac} searches for a proof using a fast tableau prover,

coded directly in \ML.  It then reconstructs the proof using Isabelle

tactics.  It is faster and more powerful than the other classical

reasoning tactics, but has major limitations too.

\begin{itemize}

\item It does not use the wrapper tacticals described above, such as

  \ttindex{addss}.

\item It ignores types, which can cause problems in \HOL.  If it applies a rule

  whose types are inappropriate, then proof reconstruction will fail.

\item It does not perform higher-order unification, as needed by the rule {\tt

    rangeI} in {\HOL} and \texttt{RepFunI} in {\ZF}.  There are often

    alternatives to such rules, for example {\tt

    range_eqI} and \texttt{RepFun_eqI}.

\item The message {\small\tt Function Var's argument not a bound variable\ }

relates to the lack of higher-order unification.  Function variables

may only be applied to parameters of the subgoal.

\item Its proof strategy is more general than \texttt{fast_tac}'s but can be

  slower.  If \texttt{blast_tac} fails or seems to be running forever, try {\tt

  fast_tac} and the other tactics described below.

\end{itemize}

%

\begin{ttbox} 

blast_tac        : claset -> int -> tactic

Blast.depth_tac  : claset -> int -> int -> tactic

Blast.trace      : bool ref \hfill{\bf initially false}

\end{ttbox}

The two tactics differ on how they bound the number of unsafe steps used in a

proof.  While \texttt{blast_tac} starts with a bound of zero and increases it

successively to~20, \texttt{Blast.depth_tac} applies a user-supplied search bound.

\begin{ttdescription}

\item[\ttindexbold{blast_tac} $cs$ $i$] tries to prove

  subgoal~$i$ using iterative deepening to increase the search bound.

\item[\ttindexbold{Blast.depth_tac} $cs$ $lim$ $i$] tries

  to prove subgoal~$i$ using a search bound of $lim$.  Often a slow

  proof using \texttt{blast_tac} can be made much faster by supplying the

  successful search bound to this tactic instead.

\item[set \ttindexbold{Blast.trace};] \index{tracing!of classical prover}

  causes the tableau prover to print a trace of its search.  At each step it

  displays the formula currently being examined and reports whether the branch

  has been closed, extended or split.

\end{ttdescription}

\subsection{Automatic tactics}\label{sec:automatic-tactics}

\begin{ttbox} 

type clasimpset = claset * simpset;

auto_tac        : clasimpset ->        tactic

force_tac       : clasimpset -> int -> tactic

auto            : unit -> unit

force           : int  -> unit

\end{ttbox}

The automatic tactics attempt to prove goals using a combination of

simplification and classical reasoning. 

\begin{ttdescription}

\item[\ttindexbold{auto_tac $(cs,ss)$}] is intended for situations where 

there are a lot of mostly trivial subgoals; it proves all the easy ones, 

leaving the ones it cannot prove.

(Unfortunately, attempting to prove the hard ones may take a long time.)  

\item[\ttindexbold{force_tac} $(cs,ss)$ $i$] is intended to prove subgoal~$i$ 

completely. It tries to apply all fancy tactics it knows about, 

performing a rather exhaustive search.

\end{ttdescription}

They must be supplied both a simpset and a claset; therefore 

they are most easily called as \texttt{Auto_tac} and \texttt{Force_tac}, which 

use the default claset and simpset (see \S\ref{sec:current-claset} below). 

For interactive use, 

the shorthand \texttt{auto();} abbreviates \texttt{by Auto_tac;} 

while \texttt{force 1;} abbreviates \texttt{by (Force_tac 1);}

\subsection{Other classical tactics}

\begin{ttbox} 

fast_tac      : claset -> int -> tactic

best_tac      : claset -> int -> tactic

slow_tac      : claset -> int -> tactic

slow_best_tac : claset -> int -> tactic

\end{ttbox}

These tactics attempt to prove a subgoal using sequent-style reasoning.

Unlike \texttt{blast_tac}, they construct proofs directly in Isabelle.  Their

effect is restricted (by \texttt{SELECT_GOAL}) to one subgoal; they either prove

this subgoal or fail.  The \texttt{slow_} versions conduct a broader

search.%

\footnote{They may, when backtracking from a failed proof attempt, undo even

  the step of proving a subgoal by assumption.}

The best-first tactics are guided by a heuristic function: typically, the

total size of the proof state.  This function is supplied in the functor call

that sets up the classical reasoner.

\begin{ttdescription}

\item[\ttindexbold{fast_tac} $cs$ $i$] applies \texttt{step_tac} using

depth-first search, to prove subgoal~$i$.

\item[\ttindexbold{best_tac} $cs$ $i$] applies \texttt{step_tac} using

best-first search, to prove subgoal~$i$.

\item[\ttindexbold{slow_tac} $cs$ $i$] applies \texttt{slow_step_tac} using

depth-first search, to prove subgoal~$i$.

\item[\ttindexbold{slow_best_tac} $cs$ $i$] applies \texttt{slow_step_tac} using

best-first search, to prove subgoal~$i$.

\end{ttdescription}

\subsection{Depth-limited automatic tactics}

\begin{ttbox} 

depth_tac  : claset -> int -> int -> tactic

deepen_tac : claset -> int -> int -> tactic

\end{ttbox}

These work by exhaustive search up to a specified depth.  Unsafe rules are

modified to preserve the formula they act on, so that it be used repeatedly.

They can prove more goals than \texttt{fast_tac} can but are much

slower, for example if the assumptions have many universal quantifiers.

The depth limits the number of unsafe steps.  If you can estimate the minimum

number of unsafe steps needed, supply this value as~$m$ to save time.

\begin{ttdescription}

\item[\ttindexbold{depth_tac} $cs$ $m$ $i$] 

tries to prove subgoal~$i$ by exhaustive search up to depth~$m$.

\item[\ttindexbold{deepen_tac} $cs$ $m$ $i$] 

tries to prove subgoal~$i$ by iterative deepening.  It calls \texttt{depth_tac}

repeatedly with increasing depths, starting with~$m$.

\end{ttdescription}

\subsection{Single-step tactics}

\begin{ttbox} 

safe_step_tac : claset -> int -> tactic

safe_tac      : claset        -> tactic

inst_step_tac : claset -> int -> tactic

step_tac      : claset -> int -> tactic

slow_step_tac : claset -> int -> tactic

\end{ttbox}

The automatic proof procedures call these tactics.  By calling them

yourself, you can execute these procedures one step at a time.

\begin{ttdescription}

\item[\ttindexbold{safe_step_tac} $cs$ $i$] performs a safe step on

  subgoal~$i$.  The safe wrapper tacticals are applied to a tactic that may

  include proof by assumption or Modus Ponens (taking care not to instantiate

  unknowns), or substitution.

\item[\ttindexbold{safe_tac} $cs$] repeatedly performs safe steps on all 

subgoals.  It is deterministic, with at most one outcome.  

\item[\ttindexbold{inst_step_tac} $cs$ $i$] is like \texttt{safe_step_tac},

but allows unknowns to be instantiated.

\item[\ttindexbold{step_tac} $cs$ $i$] is the basic step of the proof

  procedure.  The (unsafe) wrapper tacticals are applied to a tactic that tries

 \texttt{safe_tac}, \texttt{inst_step_tac}, or applies an unsafe rule from~$cs$.

\item[\ttindexbold{slow_step_tac}] 

  resembles \texttt{step_tac}, but allows backtracking between using safe

  rules with instantiation (\texttt{inst_step_tac}) and using unsafe rules.

  The resulting search space is larger.

\end{ttdescription}

\subsection{The current claset}\label{sec:current-claset}

Each theory is equipped with an implicit \emph{current

  claset}\index{claset!current}.  This is a default set of classical

rules.  The underlying idea is quite similar to that of a current

simpset described in \S\ref{sec:simp-for-dummies}; please read that

section, including its warnings.  The implicit claset can be accessed

as follows:

\begin{ttbox}

claset        : unit -> claset

claset_ref    : unit -> claset ref

claset_of     : theory -> claset

claset_ref_of : theory -> claset ref

print_claset  : theory -> unit

\end{ttbox}

The tactics

\begin{ttbox}

Blast_tac        : int -> tactic

Auto_tac         :        tactic

Force_tac        : int -> tactic

Fast_tac         : int -> tactic

Best_tac         : int -> tactic

Deepen_tac       : int -> int -> tactic

Clarify_tac      : int -> tactic

Clarify_step_tac : int -> tactic

Safe_tac         :        tactic

Safe_step_tac    : int -> tactic

Step_tac         : int -> tactic

\end{ttbox}

\indexbold{*Blast_tac}\indexbold{*Auto_tac}\indexbold{*Force_tac}

\indexbold{*Best_tac}\indexbold{*Fast_tac}%

\indexbold{*Deepen_tac}

\indexbold{*Clarify_tac}\indexbold{*Clarify_step_tac}

\indexbold{*Safe_tac}\indexbold{*Safe_step_tac}

\indexbold{*Step_tac}

make use of the current claset.  For example, \texttt{Blast_tac} is defined as 

\begin{ttbox}

fun Blast_tac i st = blast_tac (claset()) i st;

\end{ttbox}

and gets the current claset, only after it is applied to a proof

state.  The functions

\begin{ttbox}

AddSIs, AddSEs, AddSDs, AddIs, AddEs, AddDs: thm list -> unit

\end{ttbox}

\indexbold{*AddSIs} \indexbold{*AddSEs} \indexbold{*AddSDs}

\indexbold{*AddIs} \indexbold{*AddEs} \indexbold{*AddDs}

are used to add rules to the current claset.  They work exactly like their

lower case counterparts, such as \texttt{addSIs}.  Calling

\begin{ttbox}

Delrules : thm list -> unit

\end{ttbox}

deletes rules from the current claset. 

\subsection{Other useful tactics}

\index{tactics!for contradiction}

\index{tactics!for Modus Ponens}

\begin{ttbox} 

contr_tac    :             int -> tactic

mp_tac       :             int -> tactic

eq_mp_tac    :             int -> tactic

swap_res_tac : thm list -> int -> tactic

\end{ttbox}

These can be used in the body of a specialized search.

\begin{ttdescription}

\item[\ttindexbold{contr_tac} {\it i}]\index{assumptions!contradictory}

  solves subgoal~$i$ by detecting a contradiction among two assumptions of

  the form $P$ and~$\neg P$, or fail.  It may instantiate unknowns.  The

  tactic can produce multiple outcomes, enumerating all possible

  contradictions.

\item[\ttindexbold{mp_tac} {\it i}] 

is like \texttt{contr_tac}, but also attempts to perform Modus Ponens in

subgoal~$i$.  If there are assumptions $P\imp Q$ and~$P$, then it replaces

$P\imp Q$ by~$Q$.  It may instantiate unknowns.  It fails if it can do

nothing.

\item[\ttindexbold{eq_mp_tac} {\it i}] 

is like \texttt{mp_tac} {\it i}, but may not instantiate unknowns --- thus, it

is safe.

\item[\ttindexbold{swap_res_tac} {\it thms} {\it i}] refines subgoal~$i$ of

the proof state using {\it thms}, which should be a list of introduction

rules.  First, it attempts to prove the goal using \texttt{assume_tac} or

\texttt{contr_tac}.  It then attempts to apply each rule in turn, attempting

resolution and also elim-resolution with the swapped form.

\end{ttdescription}

\subsection{Creating swapped rules}

\begin{ttbox} 

swapify   : thm list -> thm list

joinrules : thm list * thm list -> (bool * thm) list

\end{ttbox}

\begin{ttdescription}

\item[\ttindexbold{swapify} {\it thms}] returns a list consisting of the

swapped versions of~{\it thms}, regarded as introduction rules.

\item[\ttindexbold{joinrules} ({\it intrs}, {\it elims})]

joins introduction rules, their swapped versions, and elimination rules for

use with \ttindex{biresolve_tac}.  Each rule is paired with~\texttt{false}

(indicating ordinary resolution) or~\texttt{true} (indicating

elim-resolution).

\end{ttdescription}

\section{Setting up the classical reasoner}\label{sec:classical-setup}

\index{classical reasoner!setting up}

Isabelle's classical object-logics, including \texttt{FOL} and \texttt{HOL}, have

the classical reasoner already set up.  When defining a new classical logic,

you should set up the reasoner yourself.  It consists of the \ML{} functor

\ttindex{ClassicalFun}, which takes the argument

signature \texttt{

                  CLASSICAL_DATA}:

\begin{ttbox} 

signature CLASSICAL_DATA =

  sig

  val mp             : thm

  val not_elim       : thm

  val swap           : thm

  val sizef          : thm -> int

  val hyp_subst_tacs : (int -> tactic) list

  end;

\end{ttbox}

Thus, the functor requires the following items:

\begin{ttdescription}

\item[\tdxbold{mp}] should be the Modus Ponens rule

$\List{\Var{P}\imp\Var{Q};\; \Var{P}} \Imp \Var{Q}$.

\item[\tdxbold{not_elim}] should be the contradiction rule

$\List{\neg\Var{P};\; \Var{P}} \Imp \Var{R}$.

\item[\tdxbold{swap}] should be the swap rule

$\List{\neg \Var{P}; \; \neg \Var{R}\Imp \Var{P}} \Imp \Var{R}$.

\item[\ttindexbold{sizef}] is the heuristic function used for best-first

search.  It should estimate the size of the remaining subgoals.  A good

heuristic function is \ttindex{size_of_thm}, which measures the size of the

proof state.  Another size function might ignore certain subgoals (say,

those concerned with type checking).  A heuristic function might simply

count the subgoals.

\item[\ttindexbold{hyp_subst_tacs}] is a list of tactics for substitution in

the hypotheses, typically created by \ttindex{HypsubstFun} (see

Chapter~\ref{substitution}).  This list can, of course, be empty.  The

tactics are assumed to be safe!

\end{ttdescription}

The functor is not at all sensitive to the formalization of the

object-logic.  It does not even examine the rules, but merely applies

them according to its fixed strategy.  The functor resides in {\tt

  Provers/classical.ML} in the Isabelle sources.

\index{classical reasoner|)}