🔧 Use a pretrained agent on real data

expe_template.lua

@@ -30,46 +30,30 @@ local args = {
     class = "smarthome.sweethome.GraphicalSensorSweetHome",
     params = {
       map_path = paths.concat("assets", "domus.svg"),
+      data_path = paths.concat('data', 'SweetHomeRaw'),
       history_length=3,
-      deterministic = true,
     },
   },
   testing_environment = {
     class = "smarthome.sweethome.GraphicalSensorSweetHome",
     params = {
       map_path = paths.concat("assets", "domus.svg"),
+      data_path = paths.concat('data', 'SweetHomeRaw-test'),
       history_length = 3,
-      deterministic = true,
     },
   },
 
   -- Agent
   agent = {
-    class = "NeuralQLearner",
-    params = {
-      preprocess = {
-        class = "Downsample",
-        params = {
-        },
-      },
-      inference = {
-        class = "Inference",
-        params = {
-        },
-      },
-      experience_pool = {
-        pool_size = 100,
-        history_length=3,
-      },
-    }
+    dump = "/home/getalp/brenon/results/2017-07-17T13:20:22-synthetic-raw-full-1/10000000/agent_10000000.t7"
   },
 
   -- Experiment
   experiment = {
     class = "BaseExperiment",
     params = {
-      steps = 10e6,
-      eval_freq = 100e3,
+      steps = 400e3,
+      eval_freq = 4e3,
       eval_steps = 5000,
     },
   },