In this paper, we propose a probabilistic model to study the interaction of bidder and seller agents in sequential automated auctions. We consider a designated “special bidder”...
iLTL is a probabilistic temporal logic that can specify properties of multiple discrete time Markov chains (DTMCs). In this paper, we describe two related tools: MarkovEstimator a...
The paper introduces symbolic bisimulations for a simple probabilistic π-calculus to overcome the infinite branching problem that still exists in checking ground bisimulations b...
Alternating-time Temporal Logic (ATL) [1] is used to reason about strategic abilities of agents. Aiming at strategies that can realistically be implemented in software, many varia...
Coarse-to-fine approaches use sequences of increasingly fine approximations to control the complexity of inference and learning. These techniques are often used in NLP and visio...