Our goal is to go deeper into the many writings on Behavior-Based
Artificial Intelligence Meyer et al., From Animals to Animats, NET
Press, 1992 and to understand the interest-rather than the mechanisms-of
learning. Our intention is to study the complexity of the behavior
of living beings from a theoretical point of view. To do so, we introduce
formal environments that model the survival issue. Then we prove
in this formal context that, many times, the extra cost imposed by
the conservation of information, even if it is relevant, is greater
than the benefit of knowing it. Consequently, in order to survive
in our abstract worlds, one must manage his knowledge in a way that
fits the evolution of the environment. Further-more, physiological
observations corroborate these purely theoretical results. Thus,
we use these results to design a parallel system in which each module
manages its knowledge in a specific way. This enables us to obtain
a virtual creature whose behavior evokes that of a biological hen.
(C) 2001 Elsevier Science B.V. All rights reserved.
%0 Journal Article
%1 Fouks2001
%A Fouks, J. D.
%A Signac, L.
%D 2001
%J ARTIFICIAL INTELLIGENCE
%K imported
%N 1-2
%P 87--116
%R 10.1016/S0004-3702(01)00133-3
%T The problem of survival from an algorithmic point of view
%V 133
%X Our goal is to go deeper into the many writings on Behavior-Based
Artificial Intelligence Meyer et al., From Animals to Animats, NET
Press, 1992 and to understand the interest-rather than the mechanisms-of
learning. Our intention is to study the complexity of the behavior
of living beings from a theoretical point of view. To do so, we introduce
formal environments that model the survival issue. Then we prove
in this formal context that, many times, the extra cost imposed by
the conservation of information, even if it is relevant, is greater
than the benefit of knowing it. Consequently, in order to survive
in our abstract worlds, one must manage his knowledge in a way that
fits the evolution of the environment. Further-more, physiological
observations corroborate these purely theoretical results. Thus,
we use these results to design a parallel system in which each module
manages its knowledge in a specific way. This enables us to obtain
a virtual creature whose behavior evokes that of a biological hen.
(C) 2001 Elsevier Science B.V. All rights reserved.
@article{Fouks2001,
abstract = {Our goal is to go deeper into the many writings on Behavior-Based
Artificial Intelligence [Meyer et al., From Animals to Animats, NET
Press, 1992] and to understand the interest-rather than the mechanisms-of
learning. Our intention is to study the complexity of the behavior
of living beings from a theoretical point of view. To do so, we introduce
formal environments that model the survival issue. Then we prove
in this formal context that, many times, the extra cost imposed by
the conservation of information, even if it is relevant, is greater
than the benefit of knowing it. Consequently, in order to survive
in our abstract worlds, one must manage his knowledge in a way that
fits the evolution of the environment. Further-more, physiological
observations corroborate these purely theoretical results. Thus,
we use these results to design a parallel system in which each module
manages its knowledge in a specific way. This enables us to obtain
a virtual creature whose behavior evokes that of a biological hen.
(C) 2001 Elsevier Science B.V. All rights reserved.},
added-at = {2007-12-16T20:00:22.000+0100},
author = {Fouks, J. D. and Signac, L.},
biburl = {https://www.bibsonomy.org/bibtex/241bd03f0041c0127cbca5bbf69e872f3/perceptron},
citedreferences = {ALPAYDIN E, 1991, TR91032 INT COMP SCI ; BROOKS RA, 1986, IEEE J ROBOTIC
AUTOM, V2, P14 ; BROOKS RA, 1991, ARTIF INTELL, V47, P139 ; CHAITIN
G, 1990, ALGORITHMIC INFORMAT ; CHRISTOS GA, 1996, NEURAL NETWORKS,
V9, P427 ; CRICK F, 1983, NATURE, V304 ; FISHER J, 1960, NATURE EARTH
PLANTS ; FOUKS JD, 1999, COMPUTER ANIMATION S, P211 ; FOUKS JD, 1999,
THEOR COMPUT SCI, V223, P121 ; HARS B, 1985, BEHAV BRAIN RES, V18,
P241 ; HENNEVIN E, 1987, BEHAV BRAIN RES, P243 ; HOLLAND J, 1975,
ADAPTATION NATURAL A ; HOLLAND JH, 1962, J ACM, V9, P297 ; JACKSON
P, 1998, INTRO EXPERT SYSTEMS ; JASTROW R, 1981, ENCHANTED LION ;
KOHONEN T, 1989, SPRINGER SERIES INFO, V8 ; MARKOVITCH S, 1988, P
5 INT C MACH LEARN, P450 ; MARR D, 1971, PHILOS T ROY SOC B, V262,
P23 ; MEYER JA, 1992, ANIMALS ANIMATS, V2 ; MICHALSKI RS, 1986, MACHINE
LEARNING ART, V2 ; MILGRAM P, 1993, RECONNAISSANCE FORME ; MINSKY
M, 1985, SOC MIND ; PENROSE R, 1989, EMPERORS NEW MIND CO ; PORTELLCORTEXS
I, 1989, BEHAV NEUROSCI, P984 ; RENDERS J, 1995, ALGORITHMES GENETIQU
; SEARLE JR, 1980, BEHAVIORAL BRAIN SCI, V3, P417 ; SMITH C, 1988,
PHYSIOL BEHAV, V43, P213 ; SMYTH B, 1995, P 14 INT JOINT C ART, P377
; THINES G, 2000, SCI AVENIR HORS SERI ; VANBAAREN J, 1997, SCIENCE
AUG, P238 ; VITANYI L, 1990, KOLMOGOROV COMPLEXIT, A, P187 ; VONFRISCH
K, 1953, DANCING BEES},
doi = {10.1016/S0004-3702(01)00133-3},
interhash = {78c86e839b7583e334dcefc68355dc6d},
intrahash = {41bd03f0041c0127cbca5bbf69e872f3},
journal = {ARTIFICIAL INTELLIGENCE},
keywords = {imported},
number = {1-2},
pages = {87--116},
timestamp = {2007-12-16T20:00:24.000+0100},
title = {The problem of survival from an algorithmic point of view},
volume = 133,
year = 2001
}