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Development of swarm behavior in artificial learning agents that adapt
  to different foraging environments

Development of swarm behavior in artificial learning agents that adapt to different foraging environments

1 April 2020
Andrea López-Incera
K. Ried
Thomas Müller
Hans J. Briegel
ArXiv (abs)PDFHTML

Papers citing "Development of swarm behavior in artificial learning agents that adapt to different foraging environments"

7 / 7 papers shown
Title
Learning to flock through reinforcement
Learning to flock through reinforcement
M. Durve
F. Peruani
A. Celani
36
27
0
05 Nov 2019
How a minimal learning agent can infer the existence of unobserved
  variables in a complex environment
How a minimal learning agent can infer the existence of unobserved variables in a complex environment
K. Ried
B. Eva
Thomas Müller
Hans J. Briegel
54
15
0
15 Oct 2019
Benchmarking projective simulation in navigation problems
Benchmarking projective simulation in navigation problems
A. Melnikov
A. Makmal
Hans J. Briegel
52
19
0
23 Apr 2018
Modelling collective motion based on the principle of agency
Modelling collective motion based on the principle of agency
K. Ried
Thomas Müller
Hans J. Briegel
30
26
0
04 Dec 2017
Meta-learning within Projective Simulation
Meta-learning within Projective Simulation
A. Makmal
A. Melnikov
Vedran Dunjko
Hans J. Briegel
45
29
0
25 Feb 2016
Projective simulation with generalization
Projective simulation with generalization
A. Melnikov
A. Makmal
Vedran Dunjko
Hans J. Briegel
44
42
0
09 Apr 2015
Projective simulation for classical learning agents: a comprehensive
  investigation
Projective simulation for classical learning agents: a comprehensive investigation
Julian Mautner
A. Makmal
D. Manzano
M. Tiersch
Hans J. Briegel
71
50
0
07 May 2013
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