Max Garagnani

Model-based Planning in Physical domains using SetGraphs

This paper proposes a non-propositional representation framework for planning in physical domains. Physical planning problems involve identifying a correct sequence (plan) of object manipulations, transformations and spatial rearrangements to achieve an assigned goal . The problem of the ramification of action effects causes most current (propositional) planning languages to have inefficient encodings of physical domains. A simpler and more efficient representation is proposed, in which actions, goals and world state are modelled using ‘setGraphs’. A set Graph is an abstract data-structure able to capture implicitly the structural and topological constraints of a physical domain. Despite being model-based, the representation also allows the use of types and propositional furmulae to specify additional domain constraints. Experimental results obtained with a specific implementation of the representation indicate significant improvements in performance in all of the domains considered.

Persuasion as a Form of Inter-Agent Negotiation

Agents in a multi-agent environment must often cooperate to achieve their objectives. In this paper an agent, B, cooperates with another agent, A, if B adopts a goal that furthers As objectives in the environment. If agents are independent and motivated by their own interests, cooperation cannot be relied upon and it may be necessary for A to persuade B to adopt a cooperative goal. This paper is concerned with the organisation and construction of persuasive argument, and examines how a rational agent comes to hold a belief, and thus, how new beliefs might be engendered and existing beliefs altered, through the process of argumentation. Argument represents an opportunity for an agent to convince a possibly sceptical or resistant audience of the veracity of its own beliefs. This ability is a vital component of rich communication, facilitating explanation, instruction, cooperation and conflict resolution. An architecture is described in which a hierarchical planner is used to develop discourse plans which can be realised in natural language using the LOLITA system. Planning is concerned with the intentional, contextual and pragmatic aspects of discourse structure as well as with the logical form of the argument and its stylistic organisation. In this paper attention is restricted to the planning of persuasive discourse, or monologue.

A Framework for Hybrid Planning

Sentential and analogical representations constitute two complementary formalisms for describing problems and domains. Experimental evidence indicates that different domain types can have their most efficient encoding in different representations. While real-world problems typically involve a combination of different types of domains, all modern planning domain description languages are purely sentential. This paper proposes a framework for planning with hybrid models, in which sentential and analogical descriptions can be integrated and used interchangeably, thereby allowing a more efficient description of realistically complex planning problems.