Carles Sierra

Negotiation Decision Functions for Autonomous Agents

We present a formal model of negotiation between autonomous agents. The purpose of the negotiation is to reach an agreement about the provision of a service by one agent for another. The model defines a range of strategies and tactics that agents can employ to generate initial offers, evaluate proposals and offer counter proposals. The model is based on computationally tractable assumptions, demonstrated in the domain of business process management and empirically evaluated.

Agents that Reason and Negotiate by Arguing

The need for negotiation in multi-agent systems stems from the requirement for agents to solve the problems posed by their interdependence upon one another. Negotiation provides a solution to these problems by giving the agents the means to resolve their conflicting objectives, corect inconsistencies in their knowledge of other agents world views, and coordinate a joint approach to domain tasks which benefits all the agents concerned. We propose a framework, based upon a system of argumentation, which permits agents to negotiate in order to establish acceptable ways of solving problems. The framework provides a formal model of argumentation-based reasoning and negotiation, details a design philosophy which ensures a clear link between the formal model and its practical instantiation, and describes a case study of this relationship for a particular class of architectures (namely those for belief-desire-intention agents).

A Framework for Argumentation-Based Negotiation

Many autonomous agents operate in domains in which the cooperation of their fellow agents cannot be guaranteed. In such domains negotiation is essential to persuade others of the value of co-operation. This paper describes a general framework for negotiation in which agents exchange proposals backed by arguments which summarise the reasons why the proposals should be accepted. The argumentation is persuasive because the exchanges are able to alter the mental state of the agents involved. The framework is inspired by our work in the domain of business process management and is explained using examples from that domain.

A Service-Oriented Negotiation Model between Autonomous Agents

We present a formal model of negotiation between autonomous agents. The purpose of the negotiation is to reach an agreement about the provision of a service by one agent for another. The model defines a range of strategies and tactics that agents can employ to generate initial offers, evaluate proposals and offer counter proposals. The model is based on computationally tractable assumptions and is demonstrated in the domain of business process management. Initial proofs about the convergence of negotiation are also presented.

Auctions and Multi-agent Systems

In an auction house, buyers and sellers coordinate so as to exchange goods following a highly structured and apparently simple procedure. These coordination conventions have evolved through the years, and are currently used in commercial institutions for exchanging diverse goods and services. In this chapter we take as an instance a traditional auction house, the Llotja (a fish market) of Blanes, and we discuss how a virtual and adaptable electronic fish market can be derived from it. In this virtual institution the mediating functions are performed by autonomous agents, and customers or vendors can be either individuals or software agents. We also show how the underlying notions can be applied to define other institutions where the participants can be software agents.

An Environment to Build and Track Agent-Based Business Collaboration

This chapter describes an environment to support the rapid assembly of agent-oriented business collaborations. Our environment allows: (i) setting up a collaboration environment as a virtual organization; (ii) reaching agreements within the collaboration environment to form short-term business collaborations; (iii) enacting business collaborations; and (iv) tracking the performance of agents within business collaborations to build their trust and reputation within the collaboration environment.

AAMAS 2016 Workshops, Best Papers, Singapore, Singapore, May 9-10, 2016, Revised Selected Papers

An agent that adopts a commitment to another agent should act so as to bring about a state of the world meeting the specifications of the commitment. Thus, by faithfully pursuing a commitment, an agent can be trusted to make sequential decisions that it believes can cause an intended state to arise. In general, though, an agent’s actions will have uncertain outcomes, and thus reaching an intended state cannot be guaranteed. For such sequential decision settings with uncertainty, therefore, commitments can only be probabilistic. We propose a semantics for the trustworthy fulfillment of a probabilistic commitment that hinges on whether the agent followed a policy that would be expected to achieve an intended state with sufficient likelihood, rather than on whether the intended state was actually reached. We have developed and evaluated algorithms that provably operationalize this semantics, with different tradeoffs between responsiveness and computational overhead. We also discuss opportunities and challenges in extending our proposed semantics to richer forms of uncertainty, and to other agent architectures besides the decision-theoretic agents that have been our initial focus of study. Finally, we consider the implications of our semantics on how trust might be established and confirmed in open agent systems.

The SADDE Methodology

This work explores the existing gap between multi-agent specification and implementation and the potential help that evolutionary programming techniques can bring in. We present a methodology to help the programmer in the transition from a set of desired global properties expressed as an equation-based model that a MAS must fulfill to an actual society of interacting agents. The evolutionary techniques are seen, within this methodology, as a procedure to tune the parameters of the population of agents in order that their aggregated behaviour maximally approaches the desired global properties.