Policy Structure

The policy framework outlines how to generate, execute, and evaluate strategies to train the mouse to perform target behaviors. It combines structured stimuli, reinforcement strategies, and evaluation

Policy Structure

The policy framework outlines how to generate, execute, and evaluate strategies to train the mouse to perform target behaviors. It combines structured stimuli, reinforcement strategies, and evaluation metrics in a systematic loop.

1. Target Behavior

The specific action or behavior that the system aims to elicit from the mouse. Examples include:

• Moving to a specific location (e.g., top-left corner of the cage).

• Performing an action (e.g., spinning in a wheel for a set duration).

2. Stimulus Sequence

A sequence of stimuli presented to the mouse to influence its behavior. Each stimulus is characterized by:

• Type:

  • Visual: LED lights (e.g., color, intensity, location).

  • Auditory: Speakers (e.g., tone frequency, duration).

  • Food Reward: Dispenser (e.g., amount, timing).

• Parameters: Fine-grained details for the stimulus, such as specific light intensity, tone pitch, or delay intervals.

• Timing: The duration and order in which stimuli are applied.

For example, a sequence may involve turning on an LED light to attract attention, playing a sound cue to reinforce the behavior, and dispensing food as a reward for completing the action.

3. Reinforcement Strategy

The reinforcement strategy defines how the system rewards or discourages behavior to guide learning:

• Reinforcement Type:

  • Positive Reinforcement: Providing a reward (e.g., food pellets) to encourage desired behavior.

  • Negative Reinforcement: Removing an aversive stimulus (e.g., sound stoppage, dimming lights) upon achieving the target behavior.

• Reinforcement Criteria:

  • Conditions under which reinforcement is delivered (e.g., "dispense food if the mouse reaches the target location within 10 seconds").

This strategy ensures that the mouse learns to associate the stimuli with rewards or relief.

4. Evaluation Metrics

Metrics are used to measure the effectiveness of the policy and track progress over time. Key metrics include:

• Success Rate: The percentage of trials where the mouse successfully performs the target behavior.

• Latency: The time taken for the mouse to initiate or complete the behavior.

• Behavioral Consistency: The degree of variability in the mouse’s behavior across multiple trials.

• Efficiency: The number of tool activations or resources required to achieve the desired outcome.

These metrics provide measurable feedback to determine whether the policy is successful or requires refinement.

5. Policy Iteration and Refinement

The system operates as a closed loop where policies are continuously improved. Steps include:

1. Execution: Apply the stimulus sequence and observe the mouse’s behavior using real-time camera feedback.

2. Evaluation: Assess the performance of the policy using success rates, latency, and consistency metrics.

3. Refinement: Modify the stimulus sequence, parameters, or reinforcement strategy based on observed outcomes.

4. Repetition: Repeat the process until the mouse reliably performs the target behavior with minimal variability.

This framework ensures that policies are systematically generated, tested, and optimized to achieve increasing levels of behavioral complexity. By combining clear targets, structured stimuli, and measurable outcomes, the system enables iterative learning and continuous improvement.