Information integration is often faced with the problem that different data sources represent the same set of the real-world objects, but give conflicting values for specific prop...
Reinforcement learning is a popular and successful framework for many agent-related problems because only limited environmental feedback is necessary for learning. While many algo...
Imitation-based learning is a general mechanism for rapid acquisition of new behaviors in autonomous agents and robots. In this paper, we propose a new approach to learning by imit...
When a software system enters the maintenance phase, the availability of accurate and consistent information about its organization can help alleviate the difficulties of program...
AI planning requires the definition of action models using a formal action and plan description language, such as the standard Planning Domain Definition Language (PDDL), as inp...