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Creating a general purpose long term memory for intelligent agents (episodic and semantic memory). Also, try to take over the world.

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Summer 2024

Researchers

Jayven Cachola and Penny Silliman

Overview:

Implemented tf-socket agent which uses TensorFlow DL networks to decide actions to take in Blind FSM. It does not do Deep Q Learning at this point (July 2024). See the paper submitted to ICAART 2025.

Extant Branches from this work:

adding-sensor-support

Jayven began work to support non-goal sensors (e.g., odd/even) but we got stuck 
because it's unclear how best to do predictions with the DL network.  Also, the 
scope of this project exceeded our remaining time. So, it's currently incomplete.

Tensorflow-layer-modifications

Penny used this branch to experiment with different DL network designs.  
No need to merge.

egreedy-tuning

We added e-Greedy to the agent.  We will likely merge this later this summer 

truncation-modification

Jayven experimented with an alternative approach to truncating predicted action 
sequences. See Journal for details.  This had no significant effect so it was not merged.

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Creating a general purpose long term memory for intelligent agents (episodic and semantic memory). Also, try to take over the world.

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