Search Results for author:
Found 4 papers, 0 papers with code
Towards learning domain-independent planning heuristics
Automated planning remains one of the most general paradigms in Artificial Intelligence, providing means of solving problems coming from a wide variety of domains.
Learning Neural Search Policies for Classical Planning
In this paper, we introduce a parametrized search algorithm template which combines various search techniques within a single routine.
Navigating Human Language Models with Synthetic Agents
We compare the trajectories contained in the text generated by the agents/model and compare that to the known ground truth of the chess board, move legality, and historical patterns of play.
Gamified and Self-Adaptive Applications for the Common Good: Research Challenges Ahead
In this paper we propose our vision on how the principles at the base of the autonomous and multi-agent systems can be exploited to design multi-challenge motivational systems to engage smart communities towards common goals.
