Language Evolution and Computation Bibliography

The problem of heterogeneous case representation poses a major obstacle to realising real-life multi-case-base reasoning (MCBR) systems. The knowledge overhead in developing and maintaining translation protocols between distributed case bases poses a serious challenge to CBR developers. In this paper, we situate CBR as a flexible problem-solving strategy that relies on several heterogeneous knowledge containers. We introduce a technique called language games to solve the interoperability issue. Our technique has two phases. The first is an eager learning phase where case bases communicate to build a shared indexing lexicon of similar cases in the distributed network. The second is the problem-solving phase where, using the distributed index, a case base can quickly consult external case bases if the local solution is insufficient. We provide a detailed description of our approach and demonstrate its effectiveness using an evaluation on a real data set from the tourism domain.

The interoperability among distributed and autonomous systems is the ultimate challenge facing the semantic web. Heterogeneity of data representation is the main source of problems. This paper proposes an innovative solution that combines lexical approaches and language games. The benefits for distributed annotation systems on the web are twofold: firstly, it will reduce the complexity of the semantic problem by moving the focus from the full-featured ontology level to the simpler lexicon level; secondly, it will avoid the drawback of a centralized third party mediator that may become a single point of failure. The main contributions of this work are concerned with (1) providing a proof of concept that language games can be an effective solution to creating and managing a distributed process of agreement on a shared lexicon, (2) describing a fully distributed service oriented architecture for language games, (3) providing empirical evidence on a real world case study in the domain of ski mountaineering.

The blogosphere refers to the distributed network of user opinions published on the WWW. Whereas centralized review sites such Amazon.com previously allowed users to post opinions on goods such as books and CDs, blogging software allows users to publish opinions on any topic without constraints on predefined schema. However, centralized review sites such as Amazon.com have one significant advantage: reviews pertaining to a single topic are collected together in one place, allowing readers to peruse a diverse range of opinions quickly. In this paper we examine how such a topic-centric view of the Blogosphere can be created. We characterise the problems in aligning similar concepts created by a set of distributed, autonomous users and describe current initiatives to solve the problem. Finally, we introduce the Tagsocratic project, a novel initiative to solve the concept alignment problem using techniques derived from research in language acquisition among distributed, autonomous agents.

Early agent research recognised that co-operating agents require access to unambiguous, semantic description of the same concept, entity or object. In fact, agent-based research on this problem anticipates many of the current initiatives of the Semantic Web project. The proposed solution involves developing a domain-specific ontology that can be mapped to other ontologies as required. In this paper we describe an alternative approach which allows autonomous agents to index shared objects without requiring ex-ante agreement on an ontology. Using a process of distributed negotiation, each agent builds a lexicon of the problem-solving competences of other agents. We present an overview of our work using this approach in three domains: a web services scenario, a multi-case-based agent approach and finally, Tagsocratic, a blog-indexing service. We then describe our future work on several open issues related to this research.

A critical issue of distributed systems is concerned with the advertising task. Current solutions require an ex-ante agreement on a common shared language. Although such an approach is feasible from the technological point of view, it is not effective in practice. The process of managing this agreement may present social implications that make the solution difficult to achieve. Recent trends in research propose a new approach based on advertising games where the agreement on a common language is produced at run time. Nevertheless up to now such a model has been studied only through simulations with standalone platforms. Our contribution is the design and the development of the first web services oriented architecture for advertising games. Therefore we approached all the issues typical of distributed systems neglected by the simulators like asynchronous communications, denial of services, and so on. Finally we present a real world application where the architecture has been deployed to support the advertising task using an advertising game model.

We advance and discuss a framework suitable to study theoretical implications and practical impact of language evolution and lexicon sharing in an open distributed multi-agent system. In our approach, the assumption of autonomy plays a key role to preserve the opportunity for the agents of local encoding of meanings. We consider the application scenario of Web services, where we conceive the problem of advertisement as a matter of sharing a denotational language. We provide a precise formulation of the agentsrsquo behavior within a game-theoretical setting. As an important consequence of our ``advertising games,'' we interpret the problem of knowledge interoperability and management in the light of evolutionary dynamics and learning in games. Our methodology is inspired by work in natural language semantics and ``language games.''

Advertising plays a key role in service oriented recommendation over a peer-to-peer network. The advertising problem can be considered as the problem of finding a common language to denote the peers' capabilities and needs. Up to now the current approaches to the problem of advertising revealed that the proposed solutions either affect the autonomy assumption or do not scale up the size of the network. We explain how an approach based on language games can be effective in dealing with the typical issue of advertising: do not require ex-ante agreement and to be responsive to the evolution of the network as an open system. In the paper we introduce the notion of advertising game, a specific language game designed to deal with the issue of supporting the emergence of a common denotation language over a network of peers. We provide the related computational model and an experimental evaluation. A positive empirical evidence is achieved by sketching a peer-to-peer recommendation service for bookmark exchanging using real data.