Title

Comparing Apples With Oranges: Evaluating Twelve Paradigms Of Agency

Abstract

We report on a study in which twelve different paradigms were used to implement agents acting in an environment which borrows elements from artificial life and multi-player strategy games. In choosing the paradigms we strived to maintain a balance between high level, logic based approaches to low level, physics oriented models; between imperative programming, declarative approaches and "learning from basics" as well as between anthropomorphic or biologically inspired models on one hand and pragmatic, performance oriented approaches on the other. Instead of strictly numerical comparisons (which can be applied to certain pairs of paradigms, but might be meaningless for others), we had chosen to view each paradigm as a methodology, and compare the design, development and debugging process of implementing the agents in the given paradigm. We found that software engineering techniques could be easily applied to some approaches, while they appeared basically meaningless for other ones. The performance of some agents were easy to predict from the start of the development, for other ones, impossible. The effort required to achieve certain functionality varied widely between the different paradigms. Although far from providing a definitive verdict on the benefits of the different paradigms, our study provided a good insight into what type of conceptual, technical or organizational problems would a development team face depending on their choice of agent paradigm. © Springer-Verlag Berlin Heidelberg 2007.

Publication Date

1-1-2007

Publication Title

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volume

4411 LNAI

Number of Pages

93-112

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1007/978-3-540-71956-4_6

Socpus ID

38049136818 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/38049136818

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