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Several tasks, such as plan reuse and agent modelling, need to interpret a given or observed plan to generate the underlying plan rationale. Although there are several previous methods that successfully extract plan rationales, they do not apply to complex plans, in particular to plans with actions that have conditional effects. In this paper, we introduce(More)
Planning actions for real robots in dynamic ,and mlcertain environments is a challenging problem. It is not viable to use a complete model of the world: it is most appropriate to achieve goals mid handle uncertainty by integrating deliberation and behavior-based reactive planning. We successfully developed a system integrating perception and action for the(More)
Our work is driven by one of the core purposes of artificial intelligence: to develop real robotic agents that achieve complex high-level goals in real-time environments. Robotic behaviors select actions as a function of the state of the robot and of the world. Designing robust and appropriate robotic behaviors is a difficult because of noise, uncertainty(More)
Intelligent problem solving requires the ability to select actions autonomously from a specific state to reach objectives. Planning algorithms provide approaches to look ahead and select a complete sequence of actions. Given a domain description consisting of preconditions and effects of the actions the planner can take, an initial state, and a goal, a(More)
1 Overview The robots used in this competition were generously provided by Sony 3]. The robots are the same as the commercial AIBO robots except for slight hardware changes and programming capabilities. These autonomous robots are about 30cm long and have 18 degrees of freedom. The neck pans 90 allowing the robot to scan the eld with its on board camera.(More)