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

A comparison study of 12 paradigms for developing embodied agents


Cite as:

L. Bölöni, L. J. Luotsinen, J. N.Ekblad, T. R. Fitz-Gibbon, C. Houchin, J. Key, MA. Khan, J. Lyu, J. Nguyen, R. Oleson, G. Stein andS. Vander Weide, and V. Trinh. A comparison study of 12 paradigms for developing embodied agents. Software: Practice and Experience, 38(3):259–305, 2008.

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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 and low level, physics oriented models; between imperative programming, declarative approaches and ``learning from basics''; between anthropomorphic or biologically inspired models on one hand and pragmatic, performance oriented approaches on the other. We have found that the choice of the paradigm determines the software development process and requires a different set of skills from the developers. In terms of raw performance, we found that the best performing paradigms were those which (a) allowed the knowledge of human experts to be explicitly transferred to the agent and (b) allowed the integration of well-known, high performance algorithms. We have found that maintaining a commitment to the chosen paradigm can be difficult; there is a strong temptation to offer shallow fixes to perceived performance problems through a ``flight into heuristics''. Our experience is that a development process without the discipline enforced by a central paradigm leads to agents which are a random collection of heuristics whose interactions are not clearly understood. Although far from providing a definitive verdict on the benefits of the different paradigms, our study provided a good insight into what kind of conceptual, technical or organizational problems would a development team face depending on their choice of agent paradigm.

BibTeX:

@article{Boloni-2008-SPE,
title = "A comparison study of 12 paradigms for developing embodied agents",
author = "L. B{\"o}l{\"o}ni and 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",
journal = "Software: Practice and Experience",
year = "2008",
volume = "38",
number = "3",
pages = "259-305",
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 and low level, physics oriented
  models; between imperative programming, declarative approaches and
  ``learning from basics''; between anthropomorphic or biologically
  inspired models on one hand and pragmatic, performance oriented
  approaches on the other.
  We have found that the choice of the paradigm determines the
  software development process and requires a different set of
  skills from the developers. In terms of raw performance, we found
  that the best performing paradigms were those which (a) allowed
  the knowledge of human experts to be explicitly transferred to the
  agent and (b) allowed the integration of well-known, high
  performance algorithms. We have found that maintaining a
  commitment to the chosen paradigm can be difficult; there is a
  strong temptation to offer shallow fixes to perceived performance
  problems through a ``flight into heuristics''. Our experience is
  that a development process without the discipline enforced by a
  central paradigm leads to agents which are a random collection of
  heuristics whose interactions are not clearly understood.
  Although far from providing a definitive verdict on the benefits
  of the different paradigms, our study provided a good insight into
  what kind of conceptual, technical or organizational problems
  would a development team face depending on their choice of agent
  paradigm.
 }
}

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