In this work we address the problem of what a good domain description for reasoning about actions should look like. We establish some postulates concerning this sore spot and point out the problems that arise when they are violated. Such problems can be overcome with the algorithms we propose.

We present a reasoning about actions framework based on a sum of epistemic logic S5 and propositional dynamic logic PDL together with a ‘no forgetting’ principle, also called perfect recall. We show that in our framework an action may be decomposed into a purely ontic action followed by a purely epistemic action. We also show that the latter is completely definable in terms of simple observations, i.e., ‘test that’ actions and that they are equivalent to public announcements of public announcement logic PAL as studied by Plaza, van Benthem and others. Finally, since these actions respect ‘no learning’ principle we show that a unified reduction method based on regression, as studied by Reiter, applies.

Traditionally, consistency is the only criterion for the quality of a theory in logicbased approaches to reasoning about actions. This work goes beyond that and contributes to the metatheory of actions by investigating what other properties a good domain description should have. We state some metatheoretical postulates concerning this sore spot. When all postulates are satisfied we call the action theory modular. Besides being easier to understand and more elaboration tolerant in McCarthy’s sense, modular theories have interesting properties. We point out the problems that arise when the postulates about modularity are violated, and propose algorithmic checks that can help the designer of an action theory to overcome them.

herzig,ivan¢ In this work we recast some design principles commonly used in software engineering and adapt them to the design and analysis of domain descriptions in reasoning about actions. We show how the informal requirements of cohesion and coupling can be turned into consistency tests of several different arrangements of modules. This gives us new criteria for domain description evaluation and clarifies the link between software and knowledge engineering in what concerns the meta-theory of actions. 1

In this work we address the problem of elaborating domain descriptions (alias action theories), in particular those that are expressed in dynamic logic. We define a general method based on contraction of formulas in a version of propositional dynamic logic with an incorporated solution to the frame problem. We present the semantics of our theory change and define syntactical operators for contracting a domain description. We establish

We investigate a modal logic of probability with a unary modal operator expressing that a proposition is more probable than its negation. Such an operator is not closed under conjunction, and its modal logic is therefore non-normal. Within this framework we study the relation of probability with other modal concepts: belief and action. We focus on the evolution of belief, and propose an integration of revision. For that framework we give a regression algorithm.

We show how in the propositional case both Reiter’s and Scherl & Levesque’s solutions to the frame problem can be modelled in dynamic epistemic logic (DEL), and provide an optimal regression algorithm for the latter. Our method is as follows: we extend Reiter’s framework by integrating observation actions and modal operators of knowledge, and encode the resulting formalism in DEL with announcement and assignment operators. By extending Lutz’ recent satisfiability-preserving reduction to our logic, we establish optimal decision procedures for both Reiter’s and Scherl & Levesque’s approaches: satisfiability is NP-complete for one agent, PSPACE-complete for multiple agents and EXPTIMEcomplete when common knowledge is involved.

Consistency check has been the only criterion for theory evaluation in logic-based approaches to reasoning about actions. This work goes beyond that and contributes to the metatheory of actions by investigating what other properties a good domain description in reasoning about actions should have. We state some metatheoretical postulates concerning this sore spot. When all postulates are satisfied together we have a modular action theory. Besides being easier to understand and more elaboration tolerant in McCarthy's sense, modular theories have interesting properties. We point out the problems that arise when the postulates about modularity are violated and propose algorithmic checks that can help the designer of an action theory to overcome them.

Like any other logical theory, domain descriptions in reasoning about actions may evolve, and thus need revision methods to adequately accommodate new information about the behavior of actions. The present work is about changing action domain descriptions in propositional dynamic logic. Its contribution is threefold: first we revisit the semantics of action theory contraction that has been done in previous work, giving more robust operators that express minimal change based on a notion of distance between Kripke-models. Second we give algorithms for syntactical action theory contraction and establish their correctness w.r.t. our semantics. Finally we state postulates for action theory contraction and assess the behavior of our operators w.r.t. them. Moreover, we also address the revision counterpart of action theory change, showing that it benefits from our semantics for