Give forager an energy mechanic so episodes terminate naturally

Previously the game ran indefinitely and relied entirely on
max_turns_per_episode to end an episode. Add start/food energy values
so an episode ends on its own when energy runs out, and mention
retro-gamer plot in the lab's training log instructions.

forager/__init__.py

@@ -1,7 +1,8 @@
 """Forager: an 8×8 grid game where an agent collects food.
 
 The agent moves in four directions collecting food that respawns on collection.
-The game runs indefinitely; retro-gamer's max_turns_per_episode controls episode length.
+The agent starts with 100 energy. Each step costs 1 energy. Collecting food
+restores 40 energy. The episode ends when energy reaches 0.
 
 Observation features for retro-gamer:
   food_dx: (food_x - agent_x) / board_width  (positive = food is to the right)
@@ -12,6 +13,8 @@ from random import randint
 from retro.game import Game
 
 BOARD_SIZE = 8
+START_ENERGY = 100
+FOOD_ENERGY = 40
 
 
 class Forager:
@@ -46,11 +49,13 @@ class Forager:
         if game.on_board(new_pos):
             self.position = new_pos
 
+        game.state['energy'] -= 1
         game.state['reward'] -= 0.01
 
         food = game.get_agent_by_name("Food")
         if self.position == food.position:
             food.relocate(game)
+            game.state['energy'] += FOOD_ENERGY
             game.state['score'] += 1
             game.state['reward'] += 1.0
 
@@ -60,6 +65,9 @@ class Forager:
         game.state['food_dx'] = (fx - ax) / bw
         game.state['food_dy'] = (fy - ay) / bh
 
+        if game.state['energy'] <= 0:
+            game.end()
+
 
 class Food:
     """The food item. Respawns when collected."""
@@ -85,7 +93,7 @@ def create_game():
     bw = bh = BOARD_SIZE
     game = Game(
         [forager, food],
-        {'score': 0, 'reward': 0.0, 'food_dx': 0.0, 'food_dy': 0.0},
+        {'score': 0, 'reward': 0.0, 'energy': START_ENERGY, 'food_dx': 0.0, 'food_dy': 0.0},
         board_size=(bw, bh),
         framerate=12,
     )

training_log.md

@@ -3,8 +3,9 @@
 Document each training attempt below. For each attempt, write your hypothesis
 before you run the experiment, then fill in the evidence and analysis after.
 
-Use `retro-gamer info runs/forager/` to see a summary of your run, and
-`cat runs/forager/training.log` to see the full log.
+Use `retro-gamer info runs/forager/` to see a summary of your run,
+`cat runs/forager/training.log` to see the full log, and
+`retro-gamer plot runs/forager/ -o runs/forager/training.png` to graph it.
 
 ---