zenggo / cog_tasks_rl_agents

Create cognitive tasks for Reinforcement Learning agents and benchmark them

Cog_tasks_RL_agents

Create cognitive tasks for Reinforcement Learning agents and benchmark them

Background

Cognitive neuroscientists run a number of experiments in the lab to probe animal and human behaviour. But, machine learning / reinforcement learning (RL) researchers use very different benchmarks to evaluate their learning agents.To make it easier to compare the behavior of animals / humans with these agents, we need to implement the cognitive neuroscience tasks in environments that are accessible to artificial reinforcement learning agents.

What is known:

• The performance of machine learning agent on machine learning task
• The performance of cognitive agent on cognitive task

What is unknown:

• The performance of machine learning agent on cognitive task
• The performance of the cognitive agent on machine learningtask.

Agents

• AuGMEnT
• LSTM
• DQN
• HER
• Monte Carlo

Tasks

Implemented in the OpenAI gym style. They are put in a independent repo here.

• 1_2AX (custom)
• 1_2AX_S (custom)
• AX_CPT (custom)
• Copy (gym)
• Copy_repeat (gym)
• Saccades (custom)
• Seq_prediction

Benchmark

Every agent is trained and evaluated on each of the tasks.