Ulrich Endriss

Negotiating socially optimal allocations of resources

A multiagent system may be thought of as an artificial society of autonomous software agents and we can apply concepts borrowed from welfare economics and social choice theory to assess the social welfare of such an agent society. In this paper, we study an abstract negotiation framework where agents can agree on multilateral deals to exchange bundles of indivisible resources. We then analyse how these deals affect social welfare for different instances of the basic framework and different interpretations of the concept of social welfare itself. In particular, we show how certain classes of deals are both sufficient and necessary to guarantee that a socially optimal allocation of resources will be reached eventually.

The CIFF Proof Procedure for Abductive Logic Programming with Constraints

We introduce a new proof procedure for abductive logic programming and present two soundness results. Our procedure extends that of Fung and Kowalski by integrating abductive reasoning with constraint solving and by relaxing the restrictions on allowed inputs for which the procedure can operate correctly. An implementation of our proof procedure is available and has been applied successfully in the context of multiagent systems.

On optimal outcomes of negotiations over resources

We analyse scenarios in which self-interested agents negotiate with each other in order to agree on deals to exchange resources. We consider two variants of the framework, one where agents can use money to compensate other agents for disadvantageous deals, and one where this is not possible. In both cases, we analyse what types of deals are necessary and sufficient to guarantee an optimal outcome of negotiation. To assess whether a given allocation of resources should be considered optimal we borrow two concepts from welfare economics: maximal social welfare in the case of the framework with money and Pareto optimality in the case of the framework without money. We also show how conditions for optimal outcomes can change depending on properties of the utility functions used by agents to represent the values they ascribe to certain sets of resources.

The KGP model of agency for global computing: computational model and prototype implementation

We present the computational counterpart of the KGP (Knowledge, Goals, Plan) declarative model of agency for Global Computing. In this context, a computational entity is seen as an agent developed using Computational Logic tools and techniques. We model a KGP agent by relying upon a collection of capabilities, which are then used to define a collection of transitions, to be used within logically specified, context sensitive control theories, which we call cycle theories. In close relationship to the declarative model, the computational model mirrors the logical architecture by specifying appropriate computational counterparts for the capabilities and using these to give the computational models of the transitions. These computational models and the one specified for the cycle theories are all based on, and are significant extensions of, existing proof procedures for abductive logic programming and logic programming with priorities. We also discuss a prototype implementation of the overall computational model for KGP.

Automated search for impossibility theorems in social choice theory: ranking sets of objects

We present a method for using standard techniques from satisfiability checking to automatically verify and discover theorems in an area of economic theory known as ranking sets of objects. The key question in this area, which has important applications in social choice theory and decision making under uncertainty, is how to extend an agents preferences over a number of objects to a preference relation over nonempty sets of such objects. Certain combinations of seemingly natural principles for this kind of preference extension can result in logical inconsistencies, which has led to a number of important impossibility theorems. We first prove a general result that shows that for a wide range of such principles, characterised by their syntactic form when expressed in a many-sorted first-order logic, any impossibility exhibited at a fixed (small) domain size will necessarily extend to the general case. We then show how to formulate candidates for impossibility theorems at a fixed domain size in propositional logic, which in turn enables us to automatically search for (general) impossibility theorems using a SAT solver. When applied to a space of 20 principles for preference extension familiar from the literature, this method yields a total of 84 impossibility theorems, including both known and nontrivial new results.

Logic-Based Agent Communication Protocols

An agent communication protocol specifies the rules of interaction governing a dialogue between agents in a multiagent system. In non-cooperative interactions (such as negotiation dialogues) occurring in open societies, the problem of checking an agent’s conformance to such a protocol is a central issue. We identify different levels of conformance (weak, exhaustive, and robust conformance) and explore, for a specific class of logic-based agents and an appropriate class of protocols, how to check an agent’s conformance to a protocol a priori, purely on the basis of the agent’s specification.

Welfare Engineering in Multiagent Systems

A multiagent system may be regarded as an artificial society of autonomous software agents. Welfare economics provides formal models of how the distribution of resources amongst the members of a society affects the well-being of that society as a whole. In multiagent systems research, the concept of social welfare is usually given a utilitarian interpretation, i.e. whatever increases the average welfare of the agents inhabiting a society is taken to be beneficial for society as well. While this is indeed appropriate for a wide range of applications, we believe that it is worthwhile to also consider some of the other social welfare orderings that have been studied in the social sciences. In this paper, we put forward an engineering approach to welfare economics in multiagent systems by investigating the following question: Given a particular social welfare ordering appropriate for some application domain, how can we design practical criteria that will allow agents to decide locally whether or not a proposed deal would further social welfare with respect to that ordering? In particular, we review previous results on negotiating Pareto optimal allocations of resources as well as allocations that maximise egalitarian social welfare under this general perspective. We also provide new results on negotiating Lorenz optimal allocations, which may be regarded as a compromise between the utilitarian and the egalitarian approaches. Finally, we briefly discuss elitist agent societies, where social welfare is tied to the welfare of the most successful agent, as well as the notion of envy-freeness.

The ciff proof procedure for abductive logic programming with constraints: Theory, implementation and experiments

We present the CIFF proof procedure for abductive logic programming with constraints, and we prove its correctness. CIFF is an extension of the IFF proof procedure for abductive logic programming, relaxing the original restrictions over variable quantification (allowedness conditions) and incorporating a constraint solver to deal with numerical constraints as in constraint logic programming. Finally, we describe the CIFF system, comparing it with state-of-the-art abductive systems and answer set solvers and showing how to use it to program some applications.

On the Communication Complexity of Multilateral Trading

We study the complexity of a multilateral negotiation framework where autonomous agents agree on a sequence of deals to exchange sets of discrete resources in order to both further their own goals and to achieve a distribution of resources that is socially optimal. When analysing such a framework, we can distinguish different aspects of complexity: How many deals are required to reach an optimal allocation of resources? How many communicative exchanges are required to agree on one such deal? How complex a communication language do we require? And finally, how complex is the reasoning task faced by each agent? This paper presents a number of results pertaining, in particular, to the first of these questions.

Multiagent resource allocation

Resource allocation in multiagent systems is a central research issue in the AgentLink community. The aim of the Technical Forum Group on Multiagent Resource Allocation (TFG-MARA) is to provide a venue for the exchange of ideas in this area and to foster collaboration between different research groups. In this article we report on the first meeting of TFG-MARA, which was held as part of the Second AgentLink III Technical Forum in Ljubljana.