From Information to Knowledge: A Role for Knowledge Networks in Decision Making and Action Selection
Abstract
:Simple Summary
Abstract
1. Introduction
1.1. Motivation
1.2. From Information to Knowledge
1.2.1. Feature Extraction
1.2.2. What Is Knowledge?
1.2.3. Memory vs. Knowledge
1.3. Brain Structures Involved in Memory Formation and Recall
2. Proposition
2.1. Knowledge Equation
- K(t): the cumulative knowledge at time “t”;
- G(t): The rate of incoming new information at time “t”. G(t) is modeled as a function of time, depending on how information is received. For instance, it could be constant, exponentially growing or influenced by other factors like attention or exposure;
- L(t): The rate of loss or forgetting old information at time “t”. This can be transient, triggered by distraction or change permanently via neuronal or synaptic degradation, as in Alzheimer’s disease;
- α: the integration rate constant, which determines how efficiently new information is integrated into the current knowledge state;
- β: the forgetting rate constant, which determines how quickly old information is forgotten.
- The term αG0/β represents the steady-state knowledge level when the rate of integrating new information and the rate of forgetting are balanced.
- The term (K0 − αG0/β) represents the transient behavior of knowledge over time, showing how it approaches the steady-state level. The rate at which K(t) approaches the steady-state is governed by β.
2.2. Knowledge Networks
2.3. Mathematical Formulation of KNs
- The activity of neural networks, including memory modules, can be described by continuous functions of time.
- The connection weights between neural networks and memory modules are constant over time.
- The contribution weights of neural networks and memory modules to the knowledge network are dynamic and vary with time.
- Neural Networks and Modules:
- Nj (t): the activity level of the i-th NN at time t;
- Mj (t): the activity level of the j-th memory module at time t;
- wij: the connection weight between the i-th NN, and the j-th memory module.
- Knowledge Networks (KNs):
- K (t): total knowledge at time t;
- αi (t): the weight of the i-th NN’s contribution to the KN at time t;
- βj (t): the weight of the j-th memory module’s contribution to the KN at time t.
- Dynamics and Interactions:
- G (t): the rate of gain of new information at time t;
- F (t): the rate of forgetting old information at time t.
- Neural Network Dynamics: The activity level of each NN, Ni (t), represents the dynamic activity levels of different neural circuits that contribute to knowledge. This can be influenced by incoming information and interaction with memory modules.
- Memory Module Dynamics: The activity level of each memory module Mj (t) represents the activity levels of memory storage systems that interact with neural networks, which can be influenced by the activity of a neural network.
- Connection Weights, (wij), represent the strength of interaction between neural networks and memory modules.
- Contribution Weights Dynamics: the weights αi (t) and βj (t) represent the dynamic importance of each neural network and memory module to the KN.
- Total Knowledge Dynamics: The total knowledge at time t, after adjusting weights, is a function of the contributions from neural networks and memory modules. The final solution for total knowledge within a KN at time t, can be modeled as
2.4. Evolution of Knowledge Networks
3. Discussion
3.1. Knowledge Acquisition and Action Selection
3.2. Establishing and Retrieving Knowledge: Attention, Sleep and Oscillations
3.3. Future Directions
4. Conclusions
Funding
Institutional Review Board Statement
Acknowledgments
Conflicts of Interest
References
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Kanwal, J.S. From Information to Knowledge: A Role for Knowledge Networks in Decision Making and Action Selection. Information 2024, 15, 487. https://doi.org/10.3390/info15080487
Kanwal JS. From Information to Knowledge: A Role for Knowledge Networks in Decision Making and Action Selection. Information. 2024; 15(8):487. https://doi.org/10.3390/info15080487
Chicago/Turabian StyleKanwal, Jagmeet S. 2024. "From Information to Knowledge: A Role for Knowledge Networks in Decision Making and Action Selection" Information 15, no. 8: 487. https://doi.org/10.3390/info15080487