using System.Collections; using System.Collections.Generic; using UnityEngine; /** Generic functions for parent Agent class. * Contains all logic for Brain-Agent communication and Agent-Environment * interaction. */ public abstract class Agent : MonoBehaviour { public Brain brain; /**< \brief The brain that will control this agent. */ /**< Use the inspector to drag the desired brain gameObject into * the Brain field */ public List observations; /**< \brief The list of the cameras the Agent uses as observations. */ /**< These cameras will be used to generate the observations */ public int maxStep; /**< \brief The number of steps the agent takes before being done. */ /**< If set to 0, the agent can only be set to done via a script. * If set to any positive integer, the agent will be set to done after that * many steps each episode. */ public bool resetOnDone = true; /**< \brief Determines the behaviour of the Agent when done.*/ /**< If true, the agent will reset when done. * If not, the agent will remain done, and no longer take actions.*/ [HideInInspector] public float reward; /**< \brief Describes the reward for the given step of the agent.*/ /**< It is reset to 0 at the beginning of every step. * Modify in AgentStep(). * Should be set to positive to reinforcement desired behavior, and * set to a negative value to punish undesireable behavior. * Additionally, the magnitude of the reward should not exceed 1.0 */ [HideInInspector] public bool done; /**< \brief Whether or not the agent is done*/ /**< Set to true when the agent has acted in some way which ends the * episode for the given agent. */ [HideInInspector] public float value; /**< \brief The current value estimate of the agent */ /**< When using an External brain, you can pass value estimates to the * agent at every step using env.Step(actions, values). * If AgentMonitor is attached to the Agent, this value will be displayed.*/ [HideInInspector] public float CumulativeReward; /**< \brief Do not modify: This keeps track of the cumulative reward.*/ [HideInInspector] public int stepCounter; /**< \brief Do not modify: This keeps track of the number of steps taken by * the agent each episode.*/ [HideInInspector] public float[] agentStoredAction; /**< \brief Do not modify: This keeps track of the last actions decided by * the brain.*/ [HideInInspector] public float[] memory; /**< \brief Do not modify directly: This is used by the brain to store * information about the previous states of the agent*/ [HideInInspector] public int id; /**< \brief Do not modify : This is the unique Identifier each agent * receives at initialization. It is used by the brain to identify * the agent.*/ void OnEnable() { id = gameObject.GetInstanceID(); if (brain != null) { brain.agents.Add(id, gameObject.GetComponent()); if (brain.brainParameters.actionSpaceType == StateType.continuous) { agentStoredAction = new float[brain.brainParameters.actionSize]; } else { agentStoredAction = new float[1]; } memory = new float[brain.brainParameters.memorySize]; } InitializeAgent(); } void OnDisable() { //Remove the agent from the list of agents of the brain brain.agents.Remove(id); } /// When GiveBrain is called, the agent unsubscribes from its /// previous brain and subscribes to the one passed in argument. /** Use this method to provide a brain to the agent via script. * Do not modify brain directly. @param b The Brain component the agent will subscribe to.*/ public void GiveBrain(Brain b) { RemoveBrain(); brain = b; brain.agents.Add(id, gameObject.GetComponent()); if (brain.brainParameters.actionSpaceType == StateType.continuous) { agentStoredAction = new float[brain.brainParameters.actionSize]; } else { agentStoredAction = new float[1]; } memory = new float[brain.brainParameters.memorySize]; } /// When RemoveBrain is called, the agent unsubscribes from its brain. /** Use this method to give a brain to an agent via script. * Do not modify brain directly. * If an agent does not have a brain, it will not update its actions.*/ public void RemoveBrain() { if (brain != null) { brain.agents.Remove(id); } } /// Initialize the agent with this method /** Must be implemented in agent-specific child class. * This method called only once when the agent is enabled. */ public virtual void InitializeAgent() { } /// Collect the states of the agent with this method /** Must be implemented in agent-specific child class. * This method called at every step and collects the state of the agent. * The lenght of the output must be the same length as the state size field * in the brain parameters of the brain the agent subscribes to. * Note : The order of the elements in the state list is important. * @returns state A list of floats corresponding to the state of the agent. */ public virtual List CollectState() { List state = new List(); return state; } /// Defines agent-specific behavior at every step depending on the action. /** Must be implemented in agent-specific child class. * Note: If your state is discrete, you need to convert your * state into a list of float with length 1. * @param action The action the agent receives from the brain. */ public virtual void AgentStep(float[] action) { } /// Defines agent-specific behaviour when done /** Must be implemented in agent-specific child class. * Is called when the Agent is done if ResetOneDone is false. * The agent will remain done. * You can use this method to remove the agent from the scene. */ public virtual void AgentOnDone() { } /// Defines agent-specific reset logic /** Must be implemented in agent-specific child class. * Is called when the academy is done. * Is called when the Agent is done if ResetOneDone is true. */ public virtual void AgentReset() { } /// Do not modify : Is used by the brain to reset the agent. public void Reset() { memory = new float[brain.brainParameters.memorySize]; CumulativeReward = 0f; stepCounter = 0; AgentReset(); } /// Do not modify : Is used by the brain to collect rewards. public float CollectReward() { return reward; } public void SetCumulativeReward() { CumulativeReward += reward; //Debug.Log(reward); } /// Do not modify : Is used by the brain to collect done. public bool CollectDone() { return done; } /// Do not modify : Is used by the brain give new action to the agent. public void UpdateAction(float[] a) { agentStoredAction = a; } /// Do not modify : Is used by the brain to make the agent perform a step. public void Step() { AgentStep(agentStoredAction); stepCounter += 1; if ((stepCounter > maxStep) && (maxStep > 0)) { done = true; } } /// Do not modify : Is used by the brain to reset the Reward. public void ResetReward() { reward = 0; } }