WIP: n-dimensional movement

Author: smejak

blockference/gridference.py

@@ -144,13 +144,33 @@ def actinf_graph(agent_network):
 class GridAgent():
     def __init__(self, grid_len, num_agents, grid_dim=2) -> None:
         self.grid = self.get_grid(grid_len, grid_dim)
+        self.grid_dim = grid_dim
+        self.no_actions = 2 * grid_dim + 1
         self.agents = self.init_agents(num_agents)
 
     def get_grid(self, grid_len, grid_dim):
         g = list(itertools.product(range(grid_len), repeat=grid_dim))
         for i, p in enumerate(g):
             g[i] += (0,)
         return g
+    
+    def move_grid(self, agent, chosen_action):
+        no_actions = 2 * self.grid_dim
+        state = list(agent.env_state)
+        new_state = state.copy()
+
+        # here
+
+        if chosen_action == 0:  # STAY
+            new_state = state
+        else:
+            if chosen_action % 2 == 1:
+                index = (chosen_action+1) / 2
+                new_state[index] = state[index] - 1 if state[index] > 0 else state[index]
+            elif chosen_action % 2 == 0:
+                index = chosen_action / 2
+                new_state[index] = state[index] + 1 if state[index] < agent.border else state[index]
+        return new_state
 
     def init_agents(self, no_agents):
         # create a dict of agents
@@ -282,4 +302,4 @@ def move_3d(self, agent, chosen_action):
         elif chosen_action == 6:  # STAY
             Y_new, X_new, Z_new = Y, X, Z
 
-        return (X_new, Y_new, Z_new)
+        return (X_new, Y_new, Z_new)

tools/model.py

@@ -15,7 +15,7 @@ class ActiveGridference(GridAgent):
     - (initial state) D -> the generative model's prior belief over hidden states at the first timestep
     - (affordances) E -> the generative model's available actions
     """
-    def __init__(self, planning_length: int = 2, env_state: tuple = (0, 0), ) -> None:
+    def __init__(self, planning_length: int = 2, env_state: tuple = (0, 0)) -> None:
         super().__init__()
         self.A = None
         self.B = None