| 1. |
- Besold, Tarek R., et al.
(författare)
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Anchoring Knowledge in Interaction : Towards a Harmonic Subsymbolic/Symbolic Framework and Architecture of Computational Cognition
- 2015
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Ingår i: Artificial General Intelligence (AGI 2015). - Cham : Springer. - 9783319213651 - 9783319213644 ; , s. 35-45
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Konferensbidrag (refereegranskat)abstract
- We outline a proposal for a research program leading to a new paradigm, architectural framework, and prototypical implementation, for the cognitively inspired anchoring of an agent's learning, knowledge formation, and higher reasoning abilities in real-world interactions: Learning through interaction in real-time in a real environment triggers the incremental accumulation and repair of knowledge that leads to the formation of theories at a higher level of abstraction. The transformations at this higher level filter down and inform the learning process as part of a permanent cycle of learning through experience, higher-order deliberation, theory formation and revision.The envisioned framework will provide a precise computational theory, algorithmic descriptions, and an implementation in cyber-physical systems, addressing the lifting of action patterns from the subsymbolic to the symbolic knowledge level, effective methods for theory formation, adaptation, and evolution, the anchoring of knowledge-level objects, realworld interactions and manipulations, and the realization and evaluation of such a system in different scenarios. The expected results can provide new foundations for future agent architectures, multi-agent systems, robotics, and cognitive systems, and can facilitate a deeper understanding of the development and interaction in human-technological settings.
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| 2. |
- Nizamani, Abdul Rahim, 1981, et al.
(författare)
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Bounded Cognitive Resources and Arbitrary Domains
- 2015
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Ingår i: Lecture Notes in Computer Science. 8th International Conference on Artificial General Intelligence, AGI 2015, Berlin, Germany, 22-25 July 2015, Proceedings / edited by Jordi Bieger, Ben Goertzel, Alexey Potapov.. - Cham : Springer International Publishing. - 0302-9743 .- 1611-3349. - 9783319213651
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Konferensbidrag (refereegranskat)abstract
- When Alice in Wonderland fell down the rabbit hole, she entered a world that was completely new to her. She gradually explored that world by observing, learning, and reasoning. This paper presents a simple system Alice in Wonderland that operates analogously. We model Alice’s Wonderland via a general notion of domain and Alice herself with a computational model including an evolving belief set along with mechanisms for observing, learning, and reasoning. The system operates autonomously, learning from arbitrary streams of facts from symbolic domains such as English grammar, propositional logic, and simple arithmetic. The main conclusion of the paper is that bounded cognitive resources can be exploited systematically in artificial general intelligence for constructing general systems that tackle the combinatorial explosion problem and operate in arbitrary symbolic domains.
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| 3. |
- Strannegård, Claes, 1962, et al.
(författare)
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Emotional Concept Development
- 2015
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Ingår i: Lecture Notes in Computer Science. Artificial General Intelligence: 8th International Conference, AGI 2015, AGI 2015, Berlin, Germany, July 22-25, 2015, Proceedings /eds. Bieger, Jordi, Ben Goertzel, and Alexey Potapov. - Cham : Springer International Publishing. - 0302-9743 .- 1611-3349. - 9783319213651
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Konferensbidrag (refereegranskat)abstract
- Artificial emotions of different varieties have been used for controlling behavior, e.g. in cognitive architectures and reinforcement learning models. We propose to use artificial emotions for a different purpose: controlling concept development. Dynamic networks with mechanisms for adding and removing nodes are more flexible than networks with a fixed topology, but if memories are added whenever a new situation arises, then these networks will soon grow out of proportion. Therefore there is a need for striking a balance that ideally ensures that only the most useful memories will be formed and preserved in the long run. Humans have a tendency to form and preserve memories of situations that are repeated frequently or experienced as emotionally intense (strongly positive or strongly negative), while removing memories that do not meet these criteria. In this paper we present a simple network model with artificial emotions that imitates these mechanisms.
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