rlaitinen
The general model for doing this is to ...
- Model Relational Frames:
- For example, Implement mechanisms for learning relational categories (e.g., same, different, comparison).
- Encode, weight, and model feedback on context-dependent and conditional relationships.
- Model Contextual Control:
- Develop models that adapt word or phrase meanings based on context conditionals, reflecting RFT’s emphasis on contextual/conditional flexibility.
- Functional Meaning:
- Incorporate talker and listener specific functional relations (e.g., operant, discriminated operant, conditional discriminated operant, compound conditional discriminated operant) to tailor NLP outputs.
- Application:
- Apply in ACT sentiment analysis, dialogue systems, and tasks requiring nuanced contextual reasoning.
- Apply in learn-channel analysis of strengths, weaknesses and deficits in performance of channel pairs
- Apply in multi-channel, learn-channel analysis and engineering of multi-scale emergence and adaptation (e.g., the HDML) Verbal Behavior structures.