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ICALP
2007
Springer

Continuous Capacities on Continuous State Spaces

9 years 11 months ago
Continuous Capacities on Continuous State Spaces
We propose axiomatizing some stochastic games, in a continuous state space setting, using continuous belief functions, resp. plausibilities, instead of measures. Then, stochastic games are just variations on continuous Markov chains. We argue that drawing at random along a belief function is the same as letting the probabilistic player P play first, then letting the non-deterministic player C play demonically. The same holds for an angelic C, using plausibilities instead. We then define a simple modal logic, and characterize simulation in terms of formulae of this logic. Finally, we show that (discounted) payoffs are defined and unique, where in the demonic case, P maximizes payoff, while C minimizes it.
Jean Goubault-Larrecq
Added 08 Jun 2010
Updated 08 Jun 2010
Type Conference
Year 2007
Where ICALP
Authors Jean Goubault-Larrecq
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