Artificial Intelligence
Handbook of theoretical computer science (vol. B)
Understanding evidential reasoning
International Journal of Approximate Reasoning - Special issue: The belief functions revisited: questions and answers
A framework for multi-valued reasoning over inconsistent viewpoints
ICSE '01 Proceedings of the 23rd International Conference on Software Engineering
Alternating-time temporal logic
Journal of the ACM (JACM)
Sequential Optimality and Coordination in Multiagent Systems
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
It Usually Works: The Temporal Logic of Stochastic Systems
Proceedings of the 7th International Conference on Computer Aided Verification
Dynamic Programming
Model checking discounted temporal properties
Theoretical Computer Science - Tools and algorithms for the construction and analysis of systems (TACAS 2004)
Quantitative μ-calculus and CTL defined over constraint semirings
Theoretical Computer Science - Quantitative aspects of programming languages (QAPL 2004)
A Temporal Logic for Stochastic Multi-Agent Systems
PRIMA '08 Proceedings of the 11th Pacific Rim International Conference on Multi-Agents: Intelligent Agents and Multi-Agent Systems
Model checking epistemic and probabilistic properties of multi-agent systems
IEA/AIE'11 Proceedings of the 24th international conference on Industrial engineering and other applications of applied intelligent systems conference on Modern approaches in applied intelligence - Volume Part II
ECSQARU'11 Proceedings of the 11th European conference on Symbolic and quantitative approaches to reasoning with uncertainty
Modeling attempt and action failure in probabilistic stit logic
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
Probabilistic stit logic and its decomposition
International Journal of Approximate Reasoning
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Most models of agents and multi-agent systems include information about possible states of the system (that defines relations between states and their external characteristics), and information about relationships between states. Qualitative models of this kind assign no numerical measures to these relationships. At the same time, quantitative models assume that the relationships are measurable, and provide numerical information about the degrees of relations. In this paper, we explore the analogies between some qualitative and quantitative models of agents/processes, especially those between transition systems and Markovian models. Typical analysis of Markovian models of processes refers only to the expected utility that can be obtained by the process. On the other hand, modal logic offers a systematic method of describing phenomena by combining various modal operators. Here, we try to exploit linguistic features, offered by propositional modal logic, for analysis of Markov chains and Markov decision processes. To this end, we propose Markov temporal logic - a multi-valued logic that extends the branching time logic CTL*.