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Comparing NARS and ...
Comparing NARS and Reinforcement Learning : An Analysis of ONA and Q-Learning Algorithms
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- Beikmohammadi, Ali, 1995- (författare)
- Stockholms universitet,Institutionen för data- och systemvetenskap
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- Magnússon, Sindri, 1987- (författare)
- Stockholms universitet,Institutionen för data- och systemvetenskap
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(creator_code:org_t)
- Springer, 2023
- 2023
- Engelska.
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Ingår i: Artificial General Intelligence. - : Springer. - 9783031334696 - 9783031334689 ; , s. 21-31
- Relaterad länk:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- In recent years, reinforcement learning (RL) has emerged as a popular approach for solving sequence-based tasks in machine learning. However, finding suitable alternatives to RL remains an exciting and innovative research area. One such alternative that has garnered attention is the Non-Axiomatic Reasoning System (NARS), which is a general-purpose cognitive reasoning framework. In this paper, we delve into the potential of NARS as a substitute for RL in solving sequence-based tasks. To investigate this, we conduct a comparative analysis of the performance of ONA as an implementation of NARS and Q-Learning in various environments that were created using the Open AI gym. The environments have different difficulty levels, ranging from simple to complex. Our results demonstrate that NARS is a promising alternative to RL, with competitive performance in diverse environments, particularly in non-deterministic ones.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
Nyckelord
- AGI
- NARS
- ONA
- Reinforcement Learning
- Q-Learning
- data- och systemvetenskap
- Computer and Systems Sciences
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)
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