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

On Argumentation Logic and Propositional Logic

This paper studies the relationship between Argumentation Logic (AL), a recently defined logic based on the study of argumentation in AI, and classical Propositional Logic (PL). In particular, it shows that AL and PL are logically equivalent in that they have the same entailment relation from any given classically consistent theory. This equivalence follows from a correspondence between the non-acceptability of (arguments for) sentences in AL and Natural Deduction (ND) proofs of the complement of these sentences. The proof of this equivalence uses a restricted form of ND proofs, where hypotheses in the application of the Reductio of Absurdum inference rule are required to be “relevant” to the absurdity derived in the rule. The paper also discusses how the argumentative re-interpretation of PL could help control the application of ex-falso quodlibet in the presence of inconsistencies

Modular-E and the role of elaboration tolerance in solving the qualification problem

AbstractWe describe Modular-E (ME), a specialized, model-theoretic logic for reasoning about actions. ME is able to represent non-deterministic domains involving concurrency, static laws (constraints), indirect effects (ramifications), and narrative information in the form of action occurrences and observations along a time line. We give formal results which characterize ME's high degree of modularity and elaboration tolerance, and show how these properties help to separate out, and provide principled solutions to, different aspects of the qualification problem. In particular, we identify the endogenous qualification problem as the problem of properly accounting for highly distributed, and potentially conflicting, causal knowledge when reasoning about the effects of actions. We show how a comprehensive solution to the endogenous qualification problem helps simplify the exogenous qualification problem — the problem of reconciling conflicts between predictions about what should be true at particular times and actual observations. More precisely, we describe how ME is able to use straightforward default reasoning techniques to solve the exogenous qualification problem largely because its robust treatments of the frame, ramification and endogenous qualification problems combine into a particular characteristic of elaboration tolerance that we formally encapsulate as a notion of “free will”

CRAFTING THE MIND OF PROSOCS AGENTS

PROSOCS agents are software agents that are built according to the KGP model of agency. KGP is used as a model for the mind of the agent, so that the agent can act autonomously using a collection of logic theories, providing the mind's reasoning functionalities. The behavior of the agent is controlled by a cycle theory that specifies the agent's preferred patterns of operation. The implementation of the mind's generic functionality in PROSOCS is worked out in such a way so it can be instantiated by the platform for different agents across applications. In this context, the development of a concrete example illustrates how an agent developer might program the generic functionality of the mind for a simple application. 20 2-4 105 131 Cited By :1

A web application to optimization of transport in military operations

Transport is an operation necessary to carry out any logistical mission, especially in times of war, peace or natural disasters. The distribution of the necessary demanded resources is done from a military unit, to the different locations or military bases. However, operational efficiency depends on the planners. In more than 60% of trips, shipping and return isn’t efficient, even between the same units. The cause is the non-consolidation of trips and the lack of return load, coming from perimeter units. Planning is done without consolidating trips and in many cases on demand. It’s presented a web application, a parametric framework to any geographical area, given the integration with applications such as Google Maps®. Computational times are reasonable, given a to hardiness to the problem. The software architecture is scalable and extensible, complying with software quality practices present in ISO 25000