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1 | using System;
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2 | using System.Collections.Generic;
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3 | using System.Linq;
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4 | using System.Text;
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5 | using System.Threading.Tasks;
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6 | using HeuristicLab.Problems.GrammaticalOptimization;
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7 |
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8 | namespace HeuristicLab.Algorithms.Bandits {
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9 | // this interface represents a policy for reinforcement learning
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10 | public interface IPolicy<in TState, TAction> {
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11 | TAction SelectAction(Random random, TState state, IEnumerable<TAction> actions);
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12 | void UpdateReward(TState state, TAction action, double reward, TState newState); // reward received when after taking action in state and new state
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13 | bool Done(TState state); // for deterministic MDP with deterministic rewards and goal to find a state with max reward
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14 | }
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15 |
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16 | public interface IGrammarPolicy : IPolicy<ReadonlySequence, ReadonlySequence> {
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17 |
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18 | }
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19 | }
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