1 files changed, 64 insertions, 0 deletions
diff --git a/tests/untried/neg/t6829.scala b/tests/untried/neg/t6829.scala
new file mode 100644
index 000000000..7cbe3c954
--- /dev/null
+++ b/tests/untried/neg/t6829.scala
@@ -0,0 +1,64 @@
+package bugs
+
+/**
+  * Created with IntelliJ IDEA.
+  * User: arya
+  * Date: 12/18/12
+  * Time: 4:17 PM
+  * To change this template use File | Settings | File Templates.
+  */
+object currenttype2 {
+
+   type Reward = Double
+
+   trait AbstractAgent[State,Action] {
+     type A = AbstractAgent[State,Action]
+     def chooseAction(s: State): Action
+     def startEpisode: A = this
+     def learn(s1: State, a: Action, s2: State, r: Reward): A
+   }
+
+   case class RewardFunction[State,Action](r: (State,Action,State) => Reward)
+
+  trait Rules[G<:GameDomain] {
+    def simulate(state: G#State, agentActions: List[(G#Agent,G#Action)]): G#State
+  }
+
+  trait AgentSimulation[G<:GameDomain] {
+    val agents: List[G#Agent]
+    val state: G#State
+    val rewards: Map[G#Agent,G#Rewards]
+    val rules: Rules[G]
+    val pastHistory: List[G#State]
+    lazy val currentHistory = state :: pastHistory
+
+    lazy val actions: Map[G#Agent,G#Action] = agents.map(a => a -> a.chooseAction(state)).toMap
+    lazy val nextState: G#State = rules.simulate(state, actions.toList)
+
+    def step: AgentSimulation[G]
+  }
+
+  case class LearningSimulation[G<:GameDomain](agents: List[G#Agent],
+                                               state: G#State,
+                                               rewards: Map[G#Agent,G#Rewards],
+                                               rules: Rules[G],
+                                               pastHistory: List[G#State] = Nil) extends AgentSimulation
+  {
+    lazy val step: LearningSimulation = {
+      val updatedAgents: List[G#Agent] = agents map { agent =>
+        val (s,a,s2) = (state,actions(agent),nextState)
+        val r = rewards(agent).r(s,a,s2)
+        agent.learn(s,a,s2,r): G#Agent
+      }
+      copy(agents = updatedAgents, state = nextState, pastHistory = currentHistory)
+    }
+  }
+
+   trait GameDomain {
+     domain =>
+     type State
+     type Action
+     type Agent = AbstractAgent[State, Action] // agent supertype
+     type Rewards = RewardFunction[State,Action]
+   }
+ }