Principles of intelligence
To understand intelligence as a whole, we look at how its components interact with each other
Active inter- connections
Adaptive representations
Multiple computational paradigms
Agent-environment computation
Multi-timescale computation
Multi-modality
Incremental assembly of capabilities
Adaptation of structure
Multimodality
Processing information through multiple sensory channels is advantageous when operating in an uncertain and non-stationary world.
Adaptive Representations
Behavioral flexibility is facilitated by adjusting the representations of world state to the agent’s environment, task, and goal. Adaptive representations ensure that a system represents aspects of the world that are most relevant to behavior in a way that is most conducive to generating that behavior.
Multi-timescale computation
Principle 6
Adaptability to environmental change is a hallmark of intelligence. A mechanistic prerequisite for such adaptation is the presence of multiple time scales of computation to detect, track, and act upon changes in the environment.
Incremental assembly of capabilities
This principle escribes the ability of intelligent agents to efficiently find multifaceted solutions to complex tasks with very high-dimensional solution spaces via the incremental assembly of solutions to simpler, low-dimensional problems in an iterative way.
Agent-environment computation
The generation of intelligent behavior leverages a flexible coupling of the agent to the environment. Through this coupling, the agent can create novel and task-related regularities. These, in turn, are exploited during the generation of intelligent behavior.
Adaptation of Structure
To respond to long-term changes in its ecological niche, an intelligent system may change its components to adapt their generalization to the novel conditions. Such changes include removal or addition of components, but also the re-factoring of existing components.
Multiple computational paradigms
Principle 2
The robustness and versatility of intelligent behavior results—at least in part—from the synergistic application of multiple computational paradigms.
Active interconnections
The components of an intelligent system must communicate via active interconnections. An interconnection is active if it shapes the information being passed, in accordance with the state of the overall system.
Principles of intelligence
SR Steinhardt
Created on March 28, 2025
Start designing with a free template
Discover more than 1500 professional designs like these:
View
Customer Empathy Map
View
Squares Diagram
View
Customer Journey Map
View
HR Organizational Chart
View
SWOT PRO
View
Branching diagram
View
Fishbone Diagram
Explore all templates
Transcript
Principles of intelligence
To understand intelligence as a whole, we look at how its components interact with each other
Active inter- connections
Adaptive representations
Multiple computational paradigms
Agent-environment computation
Multi-timescale computation
Multi-modality
Incremental assembly of capabilities
Adaptation of structure
Multimodality
Processing information through multiple sensory channels is advantageous when operating in an uncertain and non-stationary world.
Adaptive Representations
Behavioral flexibility is facilitated by adjusting the representations of world state to the agent’s environment, task, and goal. Adaptive representations ensure that a system represents aspects of the world that are most relevant to behavior in a way that is most conducive to generating that behavior.
Multi-timescale computation
Principle 6
Adaptability to environmental change is a hallmark of intelligence. A mechanistic prerequisite for such adaptation is the presence of multiple time scales of computation to detect, track, and act upon changes in the environment.
Incremental assembly of capabilities
This principle escribes the ability of intelligent agents to efficiently find multifaceted solutions to complex tasks with very high-dimensional solution spaces via the incremental assembly of solutions to simpler, low-dimensional problems in an iterative way.
Agent-environment computation
The generation of intelligent behavior leverages a flexible coupling of the agent to the environment. Through this coupling, the agent can create novel and task-related regularities. These, in turn, are exploited during the generation of intelligent behavior.
Adaptation of Structure
To respond to long-term changes in its ecological niche, an intelligent system may change its components to adapt their generalization to the novel conditions. Such changes include removal or addition of components, but also the re-factoring of existing components.
Multiple computational paradigms
Principle 2
The robustness and versatility of intelligent behavior results—at least in part—from the synergistic application of multiple computational paradigms.
Active interconnections
The components of an intelligent system must communicate via active interconnections. An interconnection is active if it shapes the information being passed, in accordance with the state of the overall system.