Special Session LAMAS 2010 Abstracts


Full Papers
Paper Nr: 5
Title:

OVERVIEW OF INTERACTIVE GENETIC PROGRAMMING APPROACHES FOR CONVERSATIONAL AGENTS

Authors:

Diana Perez-Marín and Ismael Pascual-Nieto

Abstract: Many of the existing conversational agents provide predefined answers. Therefore, the generated dialogue is quite similar for different users. Interactive genetic algorithms ask humans to provide fitness, rather than using a programmed function to compute it. This permits a better adjustment to the preferences and needs of each user. In this paper, a review of how interactive genetic algorithms can be used to provide more flexible and adaptable dialogues is presented.

Paper Nr: 6
Title:

A MULTI-AGENT MODEL FOR SIMULATING THE IMPACT OF SOCIAL STRUCTURE IN LINGUISTIC CONVERGENCE

Authors:

Gemma Bel-Enguix

Abstract: Baronchelli (Baronchelli et al., 2006) introduced a very simple model for simulating language emergence in communities of agents without any predetermined protocol. Brigatti (Brigatti, 2008) introduced the notion of Reputation in Baronchelli’s model, demonstrating how this parameter has an impact in the final results of the process. In a previous paper, we have shown that reputation is a key element in the coevolution of language and social structures in societies with asymmetrically distributed reputation. This paper presents a system for simulating linguistic convergence in static and dynamic populations with asymmetrically distributed reputation and a graphical representation of such process.

Paper Nr: 7
Title:

COGNITIVE PERSPECTIVES ON ROBOT BEHAVIOR

Authors:

Erik A. Billing

Abstract: A growing body of research within the field of intelligent robotics argues for a view of intelligence drastically different from classical artificial intelligence and cognitive science. The holistic and embodied ideas expressed by this research promote the view that intelligence is an emergent phenomenon. Similar perspectives, where numerous interactions within the system lead to emergent properties and cognitive abilities beyond that of the individual parts, can be found within many scientific fields. With the goal of understanding how behavior may be represented in robots, the present review tries to grasp what this notion of emergence really means and compare it with a selection of theories developed for analysis of human cognition, including the extended mind, distributed cognition and situated action. These theories reveal a view of intelligence where common notions of objects, goals, language and reasoning have to be rethought. A view where behavior, as well as the agent as such, is defined by the observer rather than given by their nature. Structures in the environment emerge by interaction rather than recognized. In such a view, the fundamental question is how emergent systems appear and develop, and how they may be controlled.

Paper Nr: 8
Title:

PARSING BY SIMPLE INSERTION SYSTEMS

Authors:

Gemma Bel-Enguix, Pál Dömösi and Alexander Krassovitskiy

Abstract: The aim of this paper is to initiate a new direction for the investigation of multi-agent systems. We will consider the insertion systems as very simple multi-agent systems, where the agents are consisting of their insertions. We define the systems and describe their working and main features. The central develoment of the paper is the application of such systems to parsing. Some examples to natural language processing are introduced that can illustrate the system.

Paper Nr: 9
Title:

BIOLOGICAL CONCEPT FORMATION GRAMMARS - A Flexible, Multiagent Linguistic Tool for Biological Processes

Authors:

Veronica Dahl, Pedro Barahona, Gemma Bel-Enguix and Ludwig Krippahl

Abstract: Constraint based models that are useful for processing biological information have been successfully put forward recently, e.g. for representing multi-disciplinary biological knowledge in view of cancer diagnosis, and for reconstructing RNA sequences from secondary structure. Here we generalize such results into a model for biological concept formation which can interact with heterogeneous agents through constraint-based reasoning. Our model includes linguistic agents, probabilistic agents for mining nucleic acid, and illness diagnosis agents. Information is selected automatically as a side effect of (the system) searching through applicable CHR rules, and automatically transformed when a rule triggers; decisions follow from the normal operation of the rules, and cognitive structure is given by properties that the concepts a given rule is trying to relate must satisfy. Moreover the user can declare under what circumstances a given property or properties can be relaxed. Concepts formed under relaxed properties result in output which signals not only what concepts were formed, but which of the properties associated with the construction of those concepts were satisfied and which were not. This allows us human-like flexibility while maintaining direct executability.

Paper Nr: 10
Title:

THE LINGUISTIC RELEVANCE OF LINDENMAYER SYSTEMS

Authors:

Leonor Becerra-Bonache, Suna Bensch and M. Dolores Jiménez-López

Abstract: In this paper, we investigate the linguistic relevance of Lindenmayer Systems (L Systems). L systems were introduced in the late sixties by Aristid Lindemayer as a mathematical theory of biological development. Thus they can be considered as one of the first bio-inspired models in the theory of formal languages. Two main properties in L systems are 1) the idea of parallelism in the rewriting process and 2) their expressiveness to describe non-context free structures that can be found in natural languages. Therefore, the linguistic relevance of this formalism is clearly based on three main features: bio-inspiration, parallelism and generation of non-context free languages. Despite these interesting properties, L systems have not been investigated from a linguistic point of view. With this paper we point out the interest of applying these bio-inspired systems to the description and processing of natural language.

Paper Nr: 11
Title:

PNEPS FOR SHALLOW PARSING - NEPs Extended For Parsing Applied To Shallow Parsing

Authors:

Emilio del Rosal, Alfonso Ortega de la Puente and Diana Perez-Marin

Abstract: PNEPs (Parsing Networks of Evolutionary Processors) extend NEPs with context free (instead of substituting) rules, leftmost derivation, bad terminals check and indexes to rebuild the derivation tree. It is possible to build a PNEP from any context free grammar without additional constraints, able to generate all the different derivations for ambiguous grammars with a temporal performance bound by the depth of the derivation tree. One of the main difficulties encountered by parsing techniques when building complete parsing trees for natural languages is the spatial and temporal performance of the analysis. Shallow parsing tries to overcome these difficulties. The goal of shallow parsing is to analyze the main components of the sentences (for example, noun groups, verb groups, etc.) rather than complete sentences. The current paper is mainly focused on testing the suitability of PNEPs to shallow parsing.