Ninth Workshop
The ninth Hybris Workshop will take place on June 12th-13th 2017 at the Leipzig University, Germany.
Venue
The workshop will be held at Leipzig University, Germany, Felix-Klein-Hörsaal, Paulinum, 5th floor, Augustusplatz 10.
Program
slides Abstracts
Decomposition & Learning: Recent Advances in Classical Planning
Invited talk by Joerg Hoffmann, Saarland University
Abstract:Classical Planning is a combinatorial search problem, capturing sequential decision-making in its most basic form where the solution sought is a path in a large state space graph. Decomposition and learning methods are general algorithmic ideas that have been successful in many combinatorial search problems, including but not limited to classical planning. The talk covers three recent methods developed in the speaker's research group, each of which has potential for application beyond classical planning:
- State-Space Conflict Based Learning transfers the wide-spread ideas of conflict analysis, backjumping, and nogood learning, quintessential in CSP and SAT, to state space reachability analysis. In difference to previous work in this direction, our algorithms do not assume a given solution length bound.
- Online Relaxation Refinement improves the accuracy of a heuristic function during search, based on the difficulties encountered. We show that, for recent heuristic functions from classical planning with powerful convergence properties, the approach boosts hill-climbing searches in planning, rendering them complete in theory and competitive with the state of the art in practice.
- Star-Topology Decoupled State Space Search partitions the state variables into components whose interactions form a star topology. This captures a form of "conditional independence" where leaf components are independent given the center; we show how to exploit this through search over center paths only, avoiding the multiplication of states across leaves. Optimality and completeness of standard search algorithms are preserved, and the empirical benefits are dramatic on benchmarks with a pronounced star topology.
Epistemic General Problem Solving
Invited talk by Michael Thielscher, University of New South Wales
Abstract: General problem-solving systems can understand descriptions of new problems at runtime and solve them without human intervention. I will introduce GDL-III, a formal description language for epistemic planning and general game playing. GDL-III provides a simpler representation language for actions and knowledge than existing formalisms: All that’s required are objective rules about what agents observe and can do. I will define its formal semantics and demonstrate that the language is expressive enough to model common epistemic problems. A proof will be presented that termination of GDL-III games is undecidable even when the game state space is guaranteed to be finite. I will give an overview of two reasoners for general epistemic problems that we are currently developing, and I will discuss how we plan to embed these into a hybrid control architecture for general problem-solving robots to cooperate with humans.
A Short Course in Belief Revision
Invited talk by Pavlos Peppas, University of Patras
Abstract: Thirty years ago, a new research area, now known as Belief Revision, emerged at the cross-section of Formal Philosophy, Cognitive Science, and Artificial Intelligence. In Belief Revision the problem at focus is the process by which a rational agent changes her beliefs in the light of new information. This process plays a central role in many different areas including cognitive robotics, argumentation theory, ontologies, multi-agent systems and software engineering. What makes the problem of revising beliefs non-trivial is that, in principle, it is not enough to simply add the new information to one's stock of beliefs; some of the old beliefs need to be withdrawn on pain of inconsistency. Furthermore, there is typically more than one choice on which beliefs to give up. In this tutorial we will present the most important ideas and results in the area of Belief Revision, and discuss some of its major open problems.