We present a decision making algorithm for agents that act in partially observable domains which they do not know fully. Making intelligent choices in such domains is very difficu...
Strong Cyclic Planning aims at generating iterative plans that only allow loops so far as there is a chance to reach the goal. The problem is already significantly complex for ful...
Piergiorgio Bertoli, Alessandro Cimatti, Marco Pis...
Traditional planning assumes reachability goals and/or full observability. In this paper, we propose a novel solution for safety and reachability planning with partial observabilit...
Planning in nondeterministic domains with temporally extended goals under partial observability is one of the most challenging problems in planning. Subsets of this problem have b...
Piergiorgio Bertoli, Alessandro Cimatti, Marco Pis...
We present the first real-world benchmark for sequentiallyoptimal team formation, working within the framework of a class of online football prediction games known as Fantasy Foo...
Tim Matthews, Sarvapali D. Ramchurn, Georgios Chal...