This GitHub repository hosts a comprehensive exploration of the applications of Temporal Reasoning in the realm of Artificial Intelligence. The primary focus of this project is to tackle temporal reasoning tasks by leveraging sequences of actions and observations within a Partially Observable Markov Decision Process (POMDP) environment using the Viterbi Algorithm.
The typical workflow involves taking a sequence of actions and observations within the POMDP, applying the Viterbi Algorithm, and ultimately determining the most probable sequence of hidden states that the POMDP traversed during the given sequence of actions and observations.
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Little Prince Environment: The repository includes a base version featuring the "Little Prince" environment. This serves as an introductory scenario for exploring temporal reasoning applications.
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Advanced Temporal Data: The project goes beyond the basics by providing an advanced version that revolves around speech recognition and text prediction. This challenging environment aims to push the boundaries of temporal reasoning algorithms.
