1thirteeng3/PyRlm: v0.1.0

Release v0.1.1 — Research-Oriented Release This release marks an important step in the formalization of PyRlm as an experimental research library. The focus of this version is not feature expansion, but clarity, structure, and academic usability. PyRlm is positioned explicitly as a framework for exploring Reinforcement Learning Models as architectural and conceptual constructs, rather than as a benchmark-driven Deep RL library. Highlights Clarified project scope and positioning through a revised README Improved documentation to better reflect PyRlm's conceptual and experimental nature Stable packaging and release process via PyPI Integration readiness for research workflows and citation (Zenodo-enabled release) Notes PyRlm remains experimental and subject to rapid iteration APIs may change as research directions evolve Stability is secondary to exploration and architectural clarity at this stage This release establishes PyRlm as a research-oriented foundation for further experimentation in reinforcement learning, cognitive architectures, and agent-based systems.