Applications of circumscription to formalizing common-sense knowledge
Artificial Intelligence
A deductive solution for plan generation
New Generation Computing
Planning for conjunctive goals
Artificial Intelligence
Principles of artificial intelligence
Principles of artificial intelligence
Theoretical Computer Science
Generating plans in linear logic I: actions as proofs
Theoretical Computer Science
Linear logic: its syntax and semantics
Proceedings of the workshop on Advances in linear logic
The direct simulation of Minsky machines in linear logic
Proceedings of the workshop on Advances in linear logic
Artificial Intelligence - Special volume on planning and scheduling
Journal of the ACM (JACM)
The Design and Analysis of Computer Algorithms
The Design and Analysis of Computer Algorithms
On Linear Logic Planning and Concurrency
Language and Automata Theory and Applications
On linear logic planning and concurrency
Information and Computation
Collaborative Planning with Confidentiality
Journal of Automated Reasoning
Partial deduction for linear logic—the symbolic negotiation perspective
DALT'04 Proceedings of the Second international conference on Declarative Agent Languages and Technologies
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We introduce Horn linear logic as a comprehensive logical system capable of handling the typical AI problem of making a plan of the actions to be performed by a robot so that he could get into a set of final situations, if he started with a certain initial situation. Contrary to undecidability of propositional Horn linear logic, the planning problem is proved to be decidable for a reasonably wide class of natural robot systems. The planning problem is proved to be EXPTIME-complete for the robot systems that allow actions with non-deterministic effects. Fixing a finite signature, that is a finite set of predicates and their finite domains, we get a polynomial time procedure of making plans for the robot system over this signature. The planning complexity is reduced to PSPACE for the robot systems with only pure deterministic actions. As honest numerical parameters in our algorithms we invoke the length of description of a planning task ‘from W to Z˜’ and the Kolmogorov descriptive complexity of AxT, a set of possible actions.