Guest
Presenters: Thomas Bolander (Technical University of Denmark), Thorsten Engesser (University of Freiburg), Robert Mattmüller (University of Freiburg), Sheila McIlraith (University of Toronto) Automated planning is of central concern in high-level symbolic AI research, with applications in logistics, robotics and service composition. Epistemic planning is the enrichment of automated planning with epistemic notions, including knowledge and beliefs, which not only refer to incomplete knowledge, but also beliefs about this knowledge. In general, single-agent epistemic planning considers the following problem: given my current state of knowledge, and a desirable state of knowledge, how do I get from one to the other? In multi-agent epistemic planning, the current and desirable states of knowledge might also refer to the states of knowledge of other agents, including higher-order knowledge like ensuring that agent a doesn’t get to know that agent b knows epistemic planning is of central importance
