This paper proposes an approach that enables agents to teach each other concepts from their ontologies using examples. Unlike other concept learning approaches, our approach enable...
This paper presents snlp+ebl, the first implementation of explanation based learning techniques for a partial order planner. We describe the basic learning framework of snlp+ebl, ...
In this paper, we investigate the use of hierarchical reinforcement learning (HRL) to speed up the acquisition of cooperative multi-agent tasks. We introduce a hierarchical multi-a...
Rajbala Makar, Sridhar Mahadevan, Mohammad Ghavamz...
Many learning systems suffer from the utility problem; that is, that time after learning is greater than time before learning. Discovering how to assure that learned knowledge wil...
Abstract. We discuss the application of Model-Based Diagnosis in (agentbased) planning. Here, a plan together with its executing agent is considered as a system to be diagnosed. It...