Knowledge, probability, and adversaries
Journal of the ACM (JACM)
Minimal belief and negation as failure
Artificial Intelligence
The independent choice logic for modelling multiple agents under uncertainty
Artificial Intelligence - Special issue on economic principles of multi-agent systems
Planning and acting in partially observable stochastic domains
Artificial Intelligence
Heterogeneous active agents, I: semantics
Artificial Intelligence
Conditional, probabilistic planning: a unifying algorithm and effective search control mechanisms
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Some contributions to the metatheory of the situation calculus
Journal of the ACM (JACM)
Reasoning about noisy sensors and effectors in the situation calculus
Artificial Intelligence
ACM Transactions on Computational Logic (TOCL)
Formalizing sensing actions—a transition function based approach
Artificial Intelligence
Knowlege in action: logical foundations for specifying and implementing dynamical systems
Knowlege in action: logical foundations for specifying and implementing dynamical systems
Description logics of minimal knowledge and negation as failure
ACM Transactions on Computational Logic (TOCL)
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Spinning the Semantic Web: Bringing the World Wide Web to Its Full Potential
Spinning the Semantic Web: Bringing the World Wide Web to Its Full Potential
Probabilistic Situation Calculus
Annals of Mathematics and Artificial Intelligence
Conditional Progressive Planning: A Preliminary Report
SCAI '01 Proceedings of the Seventh Scandinavian Conference on Artificial Intelligence
Consistency of Action Descriptions
PRICAI '02 Proceedings of the 7th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
Decision-Theoretic, High-Level Agent Programming in the Situation Calculus
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Belief Update in the pGOLOG Framework
KI '01 Proceedings of the Joint German/Austrian Conference on AI: Advances in Artificial Intelligence
A Deductive Database Approach to Planning in Uncertain Environments
LID '96 Proceedings of the International Workshop on Logic in Databases
A logic programming approach to knowledge-state planning, II: the DLVk system
Artificial Intelligence
Reasoning about actions in a probabilistic setting
Eighteenth national conference on Artificial intelligence
Perspectives on artificial intelligence planning
Eighteenth national conference on Artificial intelligence
On the undecidability of probabilistic planning and related stochastic optimization problems
Artificial Intelligence - special issue on planning with uncertainty and incomplete information
Artificial Intelligence - Special issue on logical formalizations and commonsense reasoning
Introduction to probabilistic automata (Computer science and applied mathematics)
Introduction to probabilistic automata (Computer science and applied mathematics)
Heterogeneous temporal probabilistic agents
ACM Transactions on Computational Logic (TOCL)
On the complexity of space bounded interactive proofs
SFCS '89 Proceedings of the 30th Annual Symposium on Foundations of Computer Science
Integrating description logics and action formalisms: first results
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 2
A faithful integration of description logics with logic programming
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Causal theories of action: a computational core
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Symbolic dynamic programming for first-order MDPs
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Combining probabilities, failures and safety in robot control
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
What is planning in the presence of sensing?
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Adding knowledge to the action description language A
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Probabilistic reasoning about actions in nonmonotonic causal theories
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
Can OWL and logic programming live together happily ever after?
ISWC'06 Proceedings of the 5th international conference on The Semantic Web
Tightly Coupled Probabilistic Description Logic Programs for the Semantic Web
Journal on Data Semantics XII
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We focus on the aspect of sensing in reasoning about actions under qualitative and probabilistic uncertainty. We first define the action language E for reasoning about actions with sensing, which has a semantics based on the autoepistemic description logic ALCKNF, and which is given a formal semantics via a system of deterministic transitions between epistemic states. As an important feature, the main computational tasks in E can be done in linear and quadratic time. We then introduce the action language E+ for reasoning about actions with sensing under qualitative and probabilistic uncertainty, which is an extension of E by actions with nondeterministic and probabilistic effects, and which is given a formal semantics in a system of deterministic, nondeterministic, and probabilistic transitions between epistemic states. We also define the notion of a belief graph, which represents the belief state of an agent after a sequence of deterministic, nondeterministic, and probabilistic actions, and which compactly represents a set of unnormalized probability distributions. Using belief graphs, we then introduce the notion of a conditional plan and its goodness for reasoning about actions under qualitative and probabilistic uncertainty. We formulate the problems of optimal and threshold conditional planning under qualitative and probabilistic uncertainty, and show that they are both uncomputable in general. We then give two algorithms for conditional planning in our framework. The first one is always sound, and it is also complete for the special case in which the relevant transitions between epistemic states are cycle-free. The second algorithm is a sound and complete solution to the problem of finite-horizon conditional planning in our framework. Under suitable assumptions, it computes every optimal finite-horizon conditional plan in polynomial time. We also describe an application of our formalism in a robotic-soccer scenario, which underlines its usefulness in realistic applications.