Adaptive Memetic Algorithms couple an evolutionary algorithm with a number of local search heuristics for improving the evolving solutions. They are part of a broad family of meta...
In this paper, we introduce a new method to recover from discrepancies in a general monitoring framework where the agent finds some explanations (points of failure) for discrepan...
Here we advocate an approach to learning hardware based on induction of finite state machines from temporal logic constraints. The method involves training on examples, constraint...
Marek A. Perkowski, Alan Mishchenko, Anatoli N. Ch...
Distributed constraint optimization (DCOP) has emerged as a useful technique for multiagent coordination. While previous DCOP work focuses on optimizing a single team objective, i...
We build the generic methodology based on machine learning and reasoning to detect the patterns of interaction between conflicting agents, including humans and their assistants. L...