# Blog posts

## 2020

Published:

Using $Q$ for imitation; differentiable decision trees and their application to RL; interactive explanations with Glass-Box.

Published:

Imitation by coaching; GAIL; human-centric vs robot-centric; DeepMimic.

Published:

Confident execution framework; explananda as differences; online decision tree induction; hybrid AI design patterns.

Published:

Integrating knowledge and machine learning; folk psychology and intentionality; soft decision trees; conceptual spaces.

Published:

Theory-of-mind as a general solution; factual and counterfactual explanation; semantic development in neural networks; cloning without action knowledge; intuition pumps.

## 2019

Published:

Goal hierarchies as rule sets; mutual information and auxiliary tasks for representation learning; model-based understanding.

Published:

Distillation and cloning; onboard swarm evolution; The Mind’s I chapters.

Published:

State representation learning in Atari; AI shortcuts and ethical debt; cloning swarms.

Published:

Model extraction; world models and representations; a MAS taxonomy.

Published:

State representation learning; emotions and qualitative regions for heuristic explanation; causal reasoning as a middle ground between statistics and mechanics; deep learning and neuroscientific discovery.

Published:

Meta-learning causal relations; decomposing explanation questions; misleading explanations; the critical influence of metrics.

Published:

Modelling other agents; DAGGER; evaluating feature importance visualisations; self, soul and circular ethics.

Published:

The theory of why-questions; fidelity versus accuracy; trees and programs as RL policies; partially-interpretable hybrids.

Published:

Decision trees for state space segmentation; lightweight manual labelling as a ‘seed’ for interpretability; the dangerous of homogenous distributed control; AI and the climate crisis.

Published:

This week didn’t involve very much reading since I focused instead on my practical investigation of the traffic coordination problem. Nonetheless, I encountered a variety of fascinating ideas.

Published:

Approximately three weeks in, I’m starting to work on a case study project that will allow me to explore some of the key ideas around multi-agent explainability – collision avoidance within a population of autonomous vehicles on road / track networks. As a result, more of my reading this week has focused specifically on the multi-agent context.