Symbolic Behaviour Benchmark (S2B)

Suite of OpenAI Gym-compatible multi-agent reinforcement learning environment centered around referntial games to benchmark for behavioral traits pertaining to symbolic behaviours, as described in Santoro et al., 2021, “Symbolic Behaviours in Artificial Intelligence”, primarily: exhibiting receptive, constructive, malleable, and separable behaviours.

Usage

gym must be installed. Environments can be created as follows, for instance, in order to test for receptivity and constructivity:

>>> import gym
>>> import symbolic_behaviour_benchmark
>>> env = gym.make(
        "SymbolicBehaviourBenchmark-ReceptiveConstructiveTestEnv-v0", 
        vocab_size=10,
        max_sentence_length=5,
        nbr_latents=5,
        min_nbr_values_per_latent=3,
        max_nbr_values_per_latent=5,
        nbr_object_centric_samples=1,
        nbr_distractors=3,
        use_communication_channel_permutations=True,
        allow_listener_query=False,
    )

Installation

Installing via pip

This package is available in PyPi as symbolic_behaviour_benchmark

pip install symbolic_behaviour_benchmark

Installing via cloning this repository

git clone https://www.github.com/Near32/SymbolicBehaviourBenchmark
cd SymbolicBehaviourBenchmark
pip install -e .