Planning with Incomplete Information

Planning is a natural domain of application for frameworks of reasoning about actions and change. In this paper we study how one such framework, the Language E, can form the basis for planning under (possibly) incomplete information. We define two types of plans: weak and safe plans, and propose a planner, called the E-Planner, which is often able to extend an initial weak plan into a safe plan even though the (explicit) information available is incomplete, e.g. for cases where the initial state is not completely known. The E-Planner is based upon a reformulation of the Language E in argumentation terms and a natural proof theory resulting from the reformulation. It uses an extension of this proof theory by means of abduction for the generation of plans and adopts argumentation-based techniques for extending weak plans into safe plans. We provide representative examples illustrating the behaviour of the E-Planner, in particular for cases where the status of fluents is incompletely known.Comment: Proceedings of the 8th International Workshop on Non-Monotonic Reasoning, April 9-11, 2000, Breckenridge, Colorad

A general approach to the implementation of action theories

Much effort has been dedicated to provide a general model of agents working in complex environments. This research focuses on the high level cognition used in determining the behavior of the agent. The language of the Situation Calculus represents a very useful way of modeling an agent’s knowledge of its environment. One of its advantages is that there exist methods to derive an executable program from a basic set of axioms. This program can then be used to determine the actions that are necessary in order to accomplish certain goal states. The main objective of this line of work is to obtain an automatic way of deriving such an executable program.Eje: Inteligencia artificialRed de Universidades con Carreras en Informática (RedUNCI

A Logic Programming Approach to Knowledge-State Planning: Semantics and Complexity

We propose a new declarative planning language, called K, which is based on principles and methods of logic programming. In this language, transitions between states of knowledge can be described, rather than transitions between completely described states of the world, which makes the language well-suited for planning under incomplete knowledge. Furthermore, it enables the use of default principles in the planning process by supporting negation as failure. Nonetheless, K also supports the representation of transitions between states of the world (i.e., states of complete knowledge) as a special case, which shows that the language is very flexible. As we demonstrate on particular examples, the use of knowledge states may allow for a natural and compact problem representation. We then provide a thorough analysis of the computational complexity of K, and consider different planning problems, including standard planning and secure planning (also known as conformant planning) problems. We show that these problems have different complexities under various restrictions, ranging from NP to NEXPTIME in the propositional case. Our results form the theoretical basis for the DLV^K system, which implements the language K on top of the DLV logic programming system.Comment: 48 pages, appeared as a Technical Report at KBS of the Vienna University of Technology, see http://www.kr.tuwien.ac.at/research/reports

A general approach to the implementation of action theories

Much effort has been dedicated to provide a general model of agents working in complex environments. This research focuses on the high level cognition used in determining the behavior of the agent. The language of the Situation Calculus represents a very useful way of modeling an agent’s knowledge of its environment. One of its advantages is that there exist methods to derive an executable program from a basic set of axioms. This program can then be used to determine the actions that are necessary in order to accomplish certain goal states. The main objective of this line of work is to obtain an automatic way of deriving such an executable program.Eje: Inteligencia artificialRed de Universidades con Carreras en Informática (RedUNCI

Open World Planning in the Situation Calculus

We describe a forward reasoning planner for open worlds that uses domain specific information for pruning its search space, as suggested by (Bacchus & Kabanza 1996; 2000). The plan-ner is written in the situation calculus-based programming language GOLOG, and it uses a situation calculus axiomati-zation of the application domain. Given a sentence to prove, the planner regresses it to an equivalent sentence about the initial situation, then invokes a theorem prover to determine whether the initial database entails and hence . We de-scribe two approaches to this theorem proving task, one based on compiling the initial database to prime implicate form, the other based on Relsat, a Davis/Putnam-based procedure. Fi-nally, we report on our experiments with open world planning based on both these approaches to the theorem proving task