Structural representation and reasoning in a hybrid cognitive architecture

@article{Licato2014StructuralRA,
  title={Structural representation and reasoning in a hybrid cognitive architecture},
  author={John Licato and Ron Sun and Selmer Bringsjord},
  journal={2014 International Joint Conference on Neural Networks (IJCNN)},
  year={2014},
  pages={891-898}
}
Psychologically and neurobiologically plausible models of knowledge often must make a difficult choice between distributed and localist representation. Distributed representation can be flexible and hold up well to noisy data, but localist models allow for structured knowledge to be represented unambiguously and reasoned over in rigorous, transparent fashion. We present a way of representing knowledge within the hybrid cognitive architecture CLARION. Our system allows both structured knowledge… 

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References

SHOWING 1-10 OF 30 REFERENCES

Relational Reasoning in a Neurally Plausible Cognitive Architecture

TLDR
The LISA model of analogical reasoning represents both relations and objects as patterns of activation distributed over semantic units, integrating these representations into propositional structures using synchrony of firing to provide an a priori account of the limitations of human working memory.

Accounting for Similarity-Based Reasoning within a Cognitive Architecture

TLDR
The paper implements this analysis in a cognitive architecture Clarion, which has previously succeeded in capturing a variety of human learning data in simulations, and demonstrates the significant role played by similarity-based reasoning.

Accounting for a variety of reasoning data within a cognitive architecture

  • R. SunXi Zhang
  • Computer Science, Psychology
    J. Exp. Theor. Artif. Intell.
  • 2006
TLDR
The exploration of both similarity-based reasoning and intuition in this cognitive architecture leads toward a more comprehensive framework of human everyday reasoning.

Connectionist Models of Rule-Based ReasoningRon

TLDR
This work shows that connectionist models of reasoning are not just ``implementations" of their symbolic counterparts, but better computational models of commonsense reasoning.

From Simple Associations to Systemic Reasoning: A Connectionist Representation of Rules, Variables and Dynamic Bindings

TLDR
It is described how a connectionist system made up of simple and slow neuron-like elements can encode millions of facts and rules involving n-ary predicates and variables, and yet perform a variety of inferences within hundreds of milliseconds.

Robust Reasoning: Integrating Rule-Based and Similarity-Based Reasoning

  • R. Sun
  • Computer Science
    Artif. Intell.
  • 1995

A Connectionist Computational Model for Epistemic and Temporal Reasoning

TLDR
This article shows that nonclassical logics, in particular propositional temporal logic and combinations of temporal and epistemic reasoning, can be effectively computed by artificial neural networks.

Compositionality and Biologically Plausible Models

TLDR
The breadth of this handbook demonstrates the diversity of approaches to compositionality that characterize current research, as well as providing detailed discussions of the problems faced by any theory purporting to describe how such systems can occur in the physical brain.

The Cambridge Handbook of Computational Psychology: Declarative/Logic-Based Cognitive Modeling

TLDR
This chapter provides an overview of the book on Introduction to Computational Cognitive Modeling and explores a range of issues associated with computational cognitive modeling and cognitive architectures.

Dual-processing accounts of reasoning, judgment, and social cognition.

TLDR
This article reviews a diverse set of proposals for dual processing in higher cognition within largely disconnected literatures in cognitive and social psychology and suggests that while some dual-process theories are concerned with parallel competing processes involving explicit and implicit knowledge systems, others are concerns with the influence of preconscious processes that contextualize and shape deliberative reasoning and decision-making.