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The Ecosystem Path ...
The Ecosystem Path to AGI
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- Strannegård, Claes, 1962 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Engsner, Niklas, 1964 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Ferrari, Pietro (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Glimmerfors, Hans (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Södergren, Marcus Hilding (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Karlsson, Tobias, 1995 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Kleve, Birger (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Skoglund, Victor (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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(creator_code:org_t)
- 2022-01-06
- 2022
- Engelska.
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Ingår i: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - Cham : Springer International Publishing. - 1611-3349 .- 0302-9743. ; 13154 LNAI, s. 269-278
- Relaterad länk:
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https://research.cha...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- We start by discussing the link between ecosystem simulators and artificial general intelligence (AGI). Then we present the open-source ecosystem simulator Ecotwin, which is based on the game engine Unity and operates on ecosystems containing inanimate objects like mountains and lakes, as well as organisms, such as animals and plants. Animal cognition is modeled by integrating three separate networks: (i) a reflex network for hard-wired reflexes; (ii) a happiness network that maps sensory data such as oxygen, water, energy, and smells, to a scalar happiness value; and (iii) a policy network for selecting actions. The policy network is trained with reinforcement learning (RL), where the reward signal is defined as the happiness difference from one time step to the next. All organisms are capable of either sexual or asexual reproduction, and they die if they run out of critical resources. We report results from three studies with Ecotwin, in which natural phenomena emerge in the models without being hardwired. First, we study a terrestrial ecosystem with wolves, deer, and grass, in which a Lotka-Volterra style population dynamics emerges. Second, we study a marine ecosystem with phytoplankton, copepods, and krill, in which a diel vertical migration behavior emerges. Third, we study an ecosystem involving lethal dangers, in which certain agents that combine RL with reflexes outperform pure RL agents.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datorteknik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Engineering (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Kommunikationssystem (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Communication Systems (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
Nyckelord
- Ecosystem
- Reflexes
- Reinforcement learning
- Neural networks
- Happiness
Publikations- och innehållstyp
- kon (ämneskategori)
- ref (ämneskategori)
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