Miguel A. Lopez-Carmona

Mobile Agents for Service Personalization in Smart Environments

Service personalization is an important goal for any smart environment. Comfort systems may be adjusted in an automatic way when a given user is present, and multimedia devices may offer a music or movie catalog with favorite contents or may even pick one of them for the user. To achieve this goal, we propose a Service Oriented Architecture implementation based on multiagent systems. We specially take advantage of the mobility features of software agents. In particular, we have developed a hierarchical, agent-based solution intended to be applicable to different smart space scenarios, ranging from small environments, like smart homes or smart offices, to large smart spaces like cities. In this paper we describe the global architecture and focus on our approach to service personalization using mobile agents that follow the users as they move through different smart spaces.

An expressive approach to fuzzy constraint based agent purchase negotiation

This paper presents a fuzzy constraint based model for bilateral multi-attribute agent purchase negotiations in competitive trading environments. Argumentation is used as a key mechanism to improve agreements, in contrast to other fuzzy constraint based models which are limited to quantitative offers and counter-offers. A set of locutions and decision mechanisms which fire them are specified, so that each agent may decide its degree of cooperation and expressiveness.

A REGION‐BASED MULTI‐ISSUE NEGOTIATION PROTOCOL FOR NONMONOTONIC UTILITY SPACES

Nonmonotonic utility spaces are found in multi‐issue negotiations where the preferences on the issues yield multiple local optima. These negotiations are specially challenging because of the inherent complexity of the search space and the difficulty of learning the opponent’s preferences. Most current solutions successfully address moderately complex preference scenarios, while solutions intended to operate in highly complex spaces are constrained by very specific preference structures. To overcome these problems, we propose the Region‐Based Multi‐issue Negotiation Protocol (RBNP) for bilateral automated negotiation. RBNP is built upon a nonmediated recursive bargaining mechanism which efficiently modulates a region‐based joint exploration of the solution space. We empirically show that RBNP produces outcomes close to the Pareto frontier in reasonable negotiation times, and show that it provides a significantly better performance when compared to a generic Similarity‐Based Multi‐issue Negotiation Protocol (SBNP), which has been successfully used in many negotiation models. We have paid attention to the strategic issues, proposing and evaluating several concession mechanisms, and analyzing the equilibrium conditions. Results suggest that RBNP may be used as a basis to develop negotiation mechanisms in nonmonotonic utility spaces.

Design and evaluation of a learning environment to effectively provide network security skills

Information system security and network security are topics of increasing importance in the information society. They are also topics where the adequate education of professionals requires the use of specific laboratory environments where the practical aspects of the discipline may be addressed. However, most approaches currently used are excessively static and lack the flexibility that the education requirements of security professionals demand. In this paper we present NEMESIS, a scenario generation framework for education on system and network security, which is based on virtualization technologies and has been designed to be open, distributed, modular, scalable and flexible. Finally, an example scenario is described and some results validating the benefits of its use in undergraduate computer security courses are shown.

Consensus policy based multi-agent negotiation

Multiagent negotiation may be understood as a consensus based group decision-making which ideally should seek the agreement of all the participants. However, there exist situations where an unanimous agreement is not possible or simply the rules imposed by the system do not seek such unanimous agreement. In this paper we propose to use a consensus policy based mediation framework (CPMF) to perform multiagent negotiations. This proposal fills a gap in the literature where protocols are in most cases indirectly biased to search for a quorum. The mechanisms proposed to perform the exploration of the negotiation space are derived from the Generalized Pattern Search non-linear optimization technique (GPS). The mediation mechanisms are guided by the aggregation of the agent preferences on the set of alternatives the mediator proposes in each negotiation round. Considerable interest is focused on the implementation of the mediation rules where we allow for a linguistic description of the type of agreements needed. We show empirically that CPMF efficiently manages negotiations following predefined consensus policies and solves situations where unanimous agreements are not viable.

A hierarchical, agent-based service oriented architecture for smart environments

Service Oriented Architectures, which allow for the integration of different subsystems and of applications running on different devices and platforms, may be very suitable to solve the problem of service personalization in large smart environments like cities, where the number of potential users and potentially available services is rapidly growing. Taking this into account, we have designed an agent-based service oriented architecture for smart spaces. Two of the greatest challenges in the design of such a solution are providing effective device, service and context federation and composition mechanisms and handling user mobility. For the first challenge, we have designed a hierarchical architecture and developed a set of inheritance, aggregation and access mechanisms for devices, services and context. To handle user mobility, we have followed three different strategies, using stationary, mobile or nomadic agents. In this paper, we describe the main aspects of our architecture and perform an experimental evaluation to determine the advantages and drawbacks of the different strategies.

A fuzzy constraint based model for automated purchase negotiations

This paper presents a fuzzy constraint based model for bilateral multi-attribute agent purchase negotiations in competitive trading environments. Fuzzy constraints are used to capture requirements and to express proposals. The proposed interaction protocol is a dialogue game protocol where argumentation is used as a key mechanism to improve agreements in contrast to other fuzzy constraint based models which are limited to quantitative offers and counter-offers. A set of locutions and decision mechanisms which fire them are fully specified, so that each agent may decide its degree of cooperation and its degree of expressiveness, which in turn may have effects on the quality of the agreement. The notions of similarity and expected valuations of products are used in order to design efficient decision mechanisms. An example of a purchase scenario and a summary of statistical tests are presented to demonstrate the proposed model.

Improving trade-offs in automated bilateral negotiations for expressive and inexpressive scenarios

In multi-issue bilateral negotiations, it is possible to make issue trade-offs to allow agents to search for win-win solutions. Different techniques may be used to perform these trade-offs. In particular, similarity criteria have been successfully used in this context. However, one drawback of similarity-based trade-offs is that this approach behaves differently depending on the knowledge each agent has about its counterpart, and depending on the order in which the different issues are considered. To address this problem, in this paper we propose three new mechanisms to improve the search for joint gains. Two of them are applicable in expressive scenarios, where agents may be willing to share preference information, while the third one is intended for inexpressive scenarios. The experimental evaluation shows how our proposals improve the efficiency and optimality of the negotiation process over previous approaches.

ADDRESSING UTILITY SPACE COMPLEXITY IN NEGOTIATIONS INVOLVING HIGHLY UNCORRELATED, CONSTRAINT-BASED UTILITY SPACES

There is an increasing interest in complex automated negotiations, where agents negotiate about multiple, interdependent issues and agent utility functions exhibit low autocorrelation. In these scenarios, the negotiation mechanisms used to find agreement solutions among agents tend to fail due to the complexity of agents’ preference spaces, and this tendency increases as the degree of autocorrelation decreases. In this paper, we propose an automated negotiation model specially tailored for highly uncorrelated utility spaces based on weighted constraints. The model relies on a mediated, auction‐based interaction protocol and a set of heuristic mechanisms for bidding and deal identification. To address the challenges raised by highly uncorrelated utility spaces, we propose to use a quality factor, which allows agents to balance utility and deal probability when placing their bids or when searching for agreement regions among these bids. Experiments show that the proposed negotiation model achieves high optimality results and low failure rates even in negotiation scenarios involving highly uncorrelated utility spaces, thus outperforming previous approaches.

Novel Insights in Agent-based Complex Automated Negotiation

This book focuses on all aspects of complex automated negotiations, which are studied in the field of autonomous agents and multi-agent systems. This book consists of two parts. I: Agent-Based Complex Automated Negotiations and II: Automated Negotiation Agents Competition. The chapters in Part I are extended versions of papers presented at the 2012 international workshop on Agent-Based Complex Automated Negotiation (ACAN), after peer reviews by three Program Committee members. Part II examines in detail ANAC 2012 (The Third Automated Negotiating Agents Competition), in which automated agents that have different negotiation strategies and are implemented by different developers are automatically negotiated in the several negotiation domains. ANAC is an international competition in which automated negotiation strategies, submitted by a number of universities and research institutes across the world, are evaluated in tournament style. The purpose of the competition is to steer the research in the area of bilateral multi-issue, closed negotiation. This book also includes the rules, results, agents and domain descriptions for ANAC 2011 as submitted by the organizers and finalists.