57,671 research outputs found
Domain independent goal recognition
Goal recognition is generally considered to follow plan recognition. The plan recognition problem is typically deļ¬ned to be that of identifying which plan in a given library of plans is being executed, given a sequence of observed actions. Once a plan has been identiļ¬ed, the goal of the plan can be assumed to follow. In this work, we address the problem of goal recognition directly, without assuming a plan library. Instead, we start with a domain description, just as is used for plan construction, and a sequence of action observations. The task, then, is to identify which possible goal state is the ultimate destination of the trajectory being observed. We present a formalisation of the problem and motivate its interest, before describing some simplifying assumptions we have made to arrive at a ļ¬rst implementation of a goal recognition system, AUTOGRAPH. We discuss the techniques employed in AUTOGRAPH to arrive at a tractable approximation of the goal recognition problem and show results for the system we have implemented
Profit Maximization and the Death of God: Theology and Economics in Benedict XVI\u27s \u3cem\u3eCharity in Truth\u3c/em\u3e
PDDL2.1: An extension of PDDL for expressing temporal planning domains
In recent years research in the planning community has moved increasingly towards application of planners to realistic problems involving both time and many types of resources. For example, interest in planning demonstrated by the space research community has inspired work in observation scheduling, planetary rover ex ploration and spacecraft control domains. Other temporal and resource-intensive domains including logistics planning, plant control and manufacturing have also helped to focus the community on the modelling and reasoning issues that must be confronted to make planning technology meet the challenges of application. The International Planning Competitions have acted as an important motivating force behind the progress that has been made in planning since 1998. The third competition (held in 2002) set the planning community the challenge of handling time and numeric resources. This necessitated the development of a modelling language capable of expressing temporal and numeric properties of planning domains. In this paper we describe the language, PDDL2.1, that was used in the competition. We describe the syntax of the language, its formal semantics and the validation of concurrent plans. We observe that PDDL2.1 has considerable modelling power --- exceeding the capabilities of current planning technology --- and presents a number of important challenges to the research community
The Automatic Inference of State Invariants in TIM
As planning is applied to larger and richer domains the effort involved in
constructing domain descriptions increases and becomes a significant burden on
the human application designer. If general planners are to be applied
successfully to large and complex domains it is necessary to provide the domain
designer with some assistance in building correctly encoded domains. One way of
doing this is to provide domain-independent techniques for extracting, from a
domain description, knowledge that is implicit in that description and that can
assist domain designers in debugging domain descriptions. This knowledge can
also be exploited to improve the performance of planners: several researchers
have explored the potential of state invariants in speeding up the performance
of domain-independent planners. In this paper we describe a process by which
state invariants can be extracted from the automatically inferred type
structure of a domain. These techniques are being developed for exploitation by
STAN, a Graphplan based planner that employs state analysis techniques to
enhance its performance
Extending the exploitation of symmetries in planning
Highly symmetric problems result in redundant search effort which can render apparently simple problems intractable. Whilst the potential benefits of symmetry-breaking have been explored in the broader search community there has been relatively little interest in the exploitation of this potential in planning. An initial exploration of the benefits of symmetry-breaking in a Graphplan framework, by Fox and Long in 1999 (Fox and Long 1999) yielded promising results but failed to take into account the importance of identifying and exploiting new symmetries that arise during the search process. In this paper we extend the symmetry exploitation ideas described in (Fox and Long 1999) to handle new symmetries and report results obtained from a range of planning problems
- ā¦