makeAgent: Create Agent.
In reinforcelearn: Reinforcement Learning

An agent consists of a policy and (optional) a value function representation and (optional) a learning algorithm.

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makeAgent(policy, val.fun = NULL, algorithm = NULL,
  preprocess = identity, replay.memory = NULL, policy.args = list(),
  val.fun.args = list(), algorithm.args = list())

`policy`	[`character(1)` \| Policy] A policy. If you pass a string the policy will be created via makePolicy.
`val.fun`	[`character(1)` \| ValueFunction] A value function representation. If you pass a string the value function will be created via makeValueFunction.
`algorithm`	[`character(1)` \| Algorithm] An algorithm. If you pass a string the algorithm will be created via makeAlgorithm.
`preprocess`	[`function`] A function which preprocesses the state so that the agent can learn on this.
`replay.memory`	[`ReplayMemory`] Replay memory for experience replay created by makeReplayMemory.
`policy.args`	[`list`] Arguments passed on to `args` in makePolicy.
`val.fun.args`	[`list`] Arguments passed on to `args` in makeValueFunction.
`algorithm.args`	[`list`] Arguments passed on to `args` in makeAlgorithm.