Term Information
Research Domain: interdisciplinary_academic
Temporal Period: 1957_philosophy
Meaning Description:

Entity capable of deliberate action with moral responsibility. Anscombe establishes agency through intentional action, where agents bear capacity for purposeful acts distinguished from mere occurrences.

Citation:
Anscombe, G.E.M. (1957). Intention. Oxford: Basil Blackwell.
Confidence: High
Context Anchors: intentional action, moral responsibility, deliberate choice, purposeful acts, philosophical agency
Version Created: Sep 06, 2025

Term Description:

Semantic evolution across philosophy, economics, and computer science as documented in foundational academic works

Selection Rationale:

Key term showing semantic evolution across multiple disciplines

Historical Significance:

Evolves from philosophical concept to economic framework to AI systems

Statistics

4

Versions

0

Analyses

Created: September 06, 2025

Created by: system

Last modified: September 06, 2025

Temporal Versions 4
Add Version
1957_philosophy Current

Entity capable of deliberate action with moral responsibility. Anscombe establishes agency through intentional action, where agents bear capacity for ...

Confidence: High
Context Anchors: intentional action, moral responsibility, deliberate choice +2 more
Created: Sep 06, 2025
1976_economics Current

Party in contractual relationship who acts on behalf of a principal with potential conflicts of interest. Introduces principal-agent framework revolut...

Confidence: High
Context Anchors: principal-agent relationship, contractual authority, information asymmetry +3 more
Created: Sep 06, 2025
1995_computer_science Current

Autonomous computational entity capable of independent action in dynamic environments. Marks transition from human role to independent computational a...

Confidence: High
Context Anchors: artificial intelligence, autonomous systems, computational entities +3 more
Created: Sep 06, 2025
2018_machine_learning Current

Learning optimization entity that maximizes cumulative reward through environmental interaction. Agents defined by ability to learn from interaction, ...

Confidence: High
Context Anchors: reinforcement learning, optimization, reward maximization +4 more
Created: Sep 06, 2025