L.J. Luotsinen, J.N. Ekblad, T.R. Fitz-Gibbon, C. Houchin, J. Key, M.A. Khan, J. Lyu, J. Nguyen, R. Oleson, G. Stein, S. Vander Weide, V. Trinh, and L. Bölöni

Comparing apples with oranges: evaluating twelve paradigms of agency


Cite as:

L.J. Luotsinen, J.N. Ekblad, T.R. Fitz-Gibbon, C. Houchin, J. Key, M.A. Khan, J. Lyu, J. Nguyen, R. Oleson, G. Stein, S. Vander Weide, V. Trinh, and L. Bölöni. Comparing apples with oranges: evaluating twelve paradigms of agency. In Fourth international Workshop on Programming Multi-Agent Systems (PROMAS-2006), pp. 51–65, May 2006.

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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.

BibTeX:

@inproceedings{Luotsinen-2006-PROMAS,
author = "L.J. Luotsinen and J.N. Ekblad and T.R. Fitz-Gibbon and C. Houchin and J. Key and M.A. Khan and J. Lyu and J. Nguyen and R. Oleson and G. Stein and S. Vander Weide and V. Trinh and L. B{\"o}l{\"o}ni",
title = "Comparing apples with oranges: evaluating twelve paradigms of agency",
booktitle = "Fourth international Workshop on Programming Multi-Agent Systems (PROMAS-2006)",
editor = "R.H. Bordini and M. Dastani and J. Dix and A.F. Segrouchni",
year = "2006",
month = "May",
pages = "51--65",
location = "Hakodate, Japan",
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.
 },
}

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