Add RL auction agent (Double DQN) and Set Transformer for team valuation
- rl_auction_agent.py: Custom Gym-free auction environment with N opponents, numpy-only Q-network with manual backprop, Double DQN policy with target network, full training loop with epsilon decay and periodic evaluation, and baseline comparison vs greedy and MILP strategies. - set_transformer.py: Team-level valuation model treating roster as an unordered set. Two modes: full PyTorch Set Transformer with ISAB/PMA when torch is available, or sklearn Bag-of-Players fallback using per-role aggregates, pairwise cosine similarities, and position entropy.
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