Constrained Object Hierarchies (COH) provides a neuroscience-inspired theoretical framework for modeling Artificial General Intelligence (AGI). As a flexible and robust foundation, COH supports the representation of general intelligent systems across diverse domains.
Formally, a COH is defined as a 9-tuple:
O = (C, A, M, N, E, I, T, G, D)
Where:
- C: Components – sub-objects organized hierarchically
- A: Attributes – state variables describing object properties
- M: Methods – executable actions associated with components
- N: Neural Components – adaptive models for learning and inference
- E: Embedding Neural Component – semantic representation of the COH
- I: Identity Constraints – rules ensuring object integrity
- T: Trigger Constraints – event-condition-action rules for dynamic behavior
- G: Goal Constraints – optimization objectives guiding intelligent behavior
- D: Constraint Daemons – real-time monitors enforcing system constraints
Based on the COH framework, the modelling process and result of a Social Judgment and Attitude Change System (Persuasion) in computational psychology are as follows:
Description and Significance: This system models how individuals process persuasive messages and update their attitudes, central to theories like the Elaboration Likelihood Model (ELM) and Heuristic-Systematic Model (HSM) [16]. Its significance in social psychology is paramount for understanding phenomena like advertising effectiveness, political persuasion, and social influence.
Analysis and Design: The model must account for two primary routes to persuasion: a central/systematic route (effortful argument analysis) and a peripheral/heuristic route (reliance on simple cues). The choice of route is determined by the receiver's motivation and ability to process the message. The design requires components for each route and triggers that route selection.
COH Modelling Solution:
-
- C:
{MessageReceiver, CurrentAttitude, PersuasionHeuristics, SystematicProcessor}
- A:
Message.arguments, Message.source_credibility, CurrentAttitude.strength, Motivation.level, Ability.level
- M:
PersuasionHeuristics.cue_processing(), SystematicProcessor.argument_scrutiny(), CurrentAttitude.update()
- N: The
CurrentAttitude (N) is an adaptive value that changes based on persuasive inputs and cognitive dissonance with other attitudes.
- E: Messages and attitudes are embedded in a semantic space (e.g., a political left-right spectrum) so that the distance between a message and the current attitude can calculate disagreement.
- I:
Attitude change is a function of the processing route. If Motivation and Ability are high, SystematicProcessor must be used. (This identity constraint is a core tenet of ELM/HSM).
- T:
ON (message_received) -> IF (Motivation.level > threshold AND Ability.level > threshold) THEN SystematicProcessor.argument_scrutiny() ELSE PersuasionHeuristics.cue_processing(). (This trigger constraint directly implements the route selection logic).
- G:
Hold correct attitudes. Minimize cognitive effort. (This dual-goal structure is the fundamental trade-off that explains the two routes).
- D: A "Dissonance" daemon monitors after an attitude change. If the new attitude conflicts with other strongly held attitudes, it triggers dissonance reduction strategies (e.g., selective exposure, attitude bolstering).
This model combines dual-process ideas with social psychology. The trigger constraint elegantly captures the central premise of persuasion models. The goal constraints explain why the two routes exist, and the daemon adds a crucial post-persuasion dynamic.
You may choose this topic and pursue one of the following routes:
📝 Essay
- Survey existing methodologies for modeling, designing, and implementing similar intelligent systems.
- Include:
- Literature synthesis
- COH framework analysis
- Critical evaluation of competing approaches
🛠️ Project
- Design and implement the system using the COH model.
- Include:
- System architecture and design
- Development and testing
- Demonstration of core functionality
🎓 Thesis
- Explore COH’s theoretical foundations in depth.
- Include:
- Proposed enhancements or extensions
- Implementation and evaluation
- Development of an advanced intelligent system grounded in COH principles
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