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Representing action: indeterminacy and ramifications
Artificial Intelligence
On the logic of causal explanation
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From functional specifications to logic programs
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AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Using temporal logics to express search control knowledge for planning
Artificial Intelligence
Computational complexity of planning and approximate planning in the presence of incompleteness
Artificial Intelligence
Formalizing sensing actions—a transition function based approach
Artificial Intelligence
Reasoning agents in dynamic domains
Logic-based artificial intelligence
Answer set programming and plan generation
Artificial Intelligence
Extending and implementing the stable model semantics
Artificial Intelligence
Polynomial-Length Planning Spans the Polynomial Hierarchy
JELIA '02 Proceedings of the European Conference on Logics in Artificial Intelligence
Planning as Satisfiability in Nondeterministic Domains
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The Ramification Problem in the Event Calculus
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
A logic programming approach to knowledge-state planning, II: the DLVk system
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SAT-based planning in complex domains: concurrency, constraints and nondeterminism
Artificial Intelligence - special issue on planning with uncertainty and incomplete information
Diagnostic reasoning with A-Prolog
Theory and Practice of Logic Programming
Conformant planning via symbolic model checking and heuristic search
Artificial Intelligence
Answer set based design of knowledge systems
Annals of Mathematics and Artificial Intelligence
Domain-dependent knowledge in answer set planning
ACM Transactions on Computational Logic (TOCL)
Theory and Practice of Logic Programming
Some Results on the Completeness of Approximation Based Reasoning
PRICAI '08 Proceedings of the 10th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Conformant planning for domains with constraints: a new approach
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 3
Asymptotically optimal encodings of conformant planning in QBF
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Conformant planning via symbolic model checking
Journal of Artificial Intelligence Research
The FF planning system: fast plan generation through heuristic search
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The 3rd international planning competition: results and analysis
Journal of Artificial Intelligence Research
Planning graph heuristics for belief space search
Journal of Artificial Intelligence Research
An extension to conformant planning using logic programming
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Fast planning through planning graph analysis
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
A causal theory of ramifications and qualifications
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Embracing causality in specifying the indirect effects of actions
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Reasoning about actions: non-deterministic effects, constraints, and qualification
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Towards an integration of answer set and constraint solving
ICLP'05 Proceedings of the 21st international conference on Logic Programming
An approximation of action theories of AL and its application to conformant planning
LPNMR'05 Proceedings of the 8th international conference on Logic Programming and Nonmonotonic Reasoning
Artificial Intelligence
Planning for multiagent using ASP-prolog
CLIMA'09 Proceedings of the 10th international conference on Computational logic in multi-agent systems
Combining answer set programming and prolog: the ASP-PROLOG system
Logic programming, knowledge representation, and nonmonotonic reasoning
A conformant planner based on approximation: CpA(H)
ACM Transactions on Intelligent Systems and Technology (TIST) - Special section on agent communication, trust in multiagent systems, intelligent tutoring and coaching systems
Advanced conflict-driven disjunctive answer set solving
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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This paper describes our methodology for building conformant planners, which is based on recent advances in the theory of action and change and answer set programming. The development of a planner for a given dynamic domain starts with encoding the knowledge about fluents and actions of the domain as an action theory D of some action language. Our choice in this paper is AL - an action language with dynamic and static causal laws and executability conditions. An action theory D of AL defines a transition diagram T(D) containing all the possible trajectories of the domain. A transition belongs to T(D) iff the execution of the action a in the state s may move the domain to the state s^'. The second step in the planner development consists in finding a deterministic transition diagram T^l^p(D) such that nodes of T^l^p(D) are partial states of D, its arcs are labeled by actions, and a path in T^l^p(D) from an initial partial state @d^0 to a partial state satisfying the goal @d^f corresponds to a conformant plan for @d^0 and @d^f in T(D). The transition diagram T^l^p(D) is called an 'approximation' of T(D). We claim that a concise description of an approximation of T(D) can often be given by a logic program @p(D) under the answer sets semantics. Moreover, complex initial situations and constraints on plans can be also expressed by logic programming rules and included in @p(D). If this is possible then the problem of finding a parallel or sequential conformant plan can be reduced to computing answer sets of @p(D). This can be done by general purpose answer set solvers. If plans are sequential and long then this method can be too time consuming. In this case, @p(D) is used as a specification for a procedural graph searching conformant planning algorithm. The paper illustrates this methodology by building several conformant planners which work for domains with complex relationship between the fluents. The efficiency of the planners is experimentally evaluated on a number of new and old benchmarks. In addition we show that for a subclass of action theories of AL our planners are complete, i.e., if in T^l^p(D) we cannot get from @d^0 to a state satisfying the goal @d^f then there is no conformant plan for @d^0 and @d^f in T(D).