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Added simpleReflexAgentProgram to vacuumworld.ipynb #820

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276ec26
Added simpleReflexAgentProgram to vacuumworld.ipynb
nouman-10 Mar 7, 2018
e92df12
fixed a styling issue
nouman-10 Mar 7, 2018
7d392e8
Fixed a type
nouman-10 Mar 8, 2018
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216 changes: 185 additions & 31 deletions vacuum_world.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -73,7 +73,7 @@
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Expand All @@ -90,23 +90,161 @@
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"\n",
"<div class=\"highlight\"><pre><span></span><span class=\"k\">class</span> <span class=\"nc\">TrivialVacuumEnvironment</span><span class=\"p\">(</span><span class=\"n\">Environment</span><span class=\"p\">):</span>\n",
"\n",
" <span class=\"sd\">&quot;&quot;&quot;This environment has two locations, A and B. Each can be Dirty</span>\n",
"<span class=\"sd\"> or Clean. The agent perceives its location and the location&#39;s</span>\n",
"<span class=\"sd\"> status. This serves as an example of how to implement a simple</span>\n",
"<span class=\"sd\"> Environment.&quot;&quot;&quot;</span>\n",
"\n",
" <span class=\"k\">def</span> <span class=\"fm\">__init__</span><span class=\"p\">(</span><span class=\"bp\">self</span><span class=\"p\">):</span>\n",
" <span class=\"nb\">super</span><span class=\"p\">()</span><span class=\"o\">.</span><span class=\"fm\">__init__</span><span class=\"p\">()</span>\n",
" <span class=\"bp\">self</span><span class=\"o\">.</span><span class=\"n\">status</span> <span class=\"o\">=</span> <span class=\"p\">{</span><span class=\"n\">loc_A</span><span class=\"p\">:</span> <span class=\"n\">random</span><span class=\"o\">.</span><span class=\"n\">choice</span><span class=\"p\">([</span><span class=\"s1\">&#39;Clean&#39;</span><span class=\"p\">,</span> <span class=\"s1\">&#39;Dirty&#39;</span><span class=\"p\">]),</span>\n",
" <span class=\"n\">loc_B</span><span class=\"p\">:</span> <span class=\"n\">random</span><span class=\"o\">.</span><span class=\"n\">choice</span><span class=\"p\">([</span><span class=\"s1\">&#39;Clean&#39;</span><span class=\"p\">,</span> <span class=\"s1\">&#39;Dirty&#39;</span><span class=\"p\">])}</span>\n",
"\n",
" <span class=\"k\">def</span> <span class=\"nf\">thing_classes</span><span class=\"p\">(</span><span class=\"bp\">self</span><span class=\"p\">):</span>\n",
" <span class=\"k\">return</span> <span class=\"p\">[</span><span class=\"n\">Wall</span><span class=\"p\">,</span> <span class=\"n\">Dirt</span><span class=\"p\">,</span> <span class=\"n\">ReflexVacuumAgent</span><span class=\"p\">,</span> <span class=\"n\">RandomVacuumAgent</span><span class=\"p\">,</span>\n",
" <span class=\"n\">TableDrivenVacuumAgent</span><span class=\"p\">,</span> <span class=\"n\">ModelBasedVacuumAgent</span><span class=\"p\">]</span>\n",
"\n",
" <span class=\"k\">def</span> <span class=\"nf\">percept</span><span class=\"p\">(</span><span class=\"bp\">self</span><span class=\"p\">,</span> <span class=\"n\">agent</span><span class=\"p\">):</span>\n",
" <span class=\"sd\">&quot;&quot;&quot;Returns the agent&#39;s location, and the location status (Dirty/Clean).&quot;&quot;&quot;</span>\n",
" <span class=\"k\">return</span> <span class=\"p\">(</span><span class=\"n\">agent</span><span class=\"o\">.</span><span class=\"n\">location</span><span class=\"p\">,</span> <span class=\"bp\">self</span><span class=\"o\">.</span><span class=\"n\">status</span><span class=\"p\">[</span><span class=\"n\">agent</span><span class=\"o\">.</span><span class=\"n\">location</span><span class=\"p\">])</span>\n",
"\n",
" <span class=\"k\">def</span> <span class=\"nf\">execute_action</span><span class=\"p\">(</span><span class=\"bp\">self</span><span class=\"p\">,</span> <span class=\"n\">agent</span><span class=\"p\">,</span> <span class=\"n\">action</span><span class=\"p\">):</span>\n",
" <span class=\"sd\">&quot;&quot;&quot;Change agent&#39;s location and/or location&#39;s status; track performance.</span>\n",
"<span class=\"sd\"> Score 10 for each dirt cleaned; -1 for each move.&quot;&quot;&quot;</span>\n",
" <span class=\"k\">if</span> <span class=\"n\">action</span> <span class=\"o\">==</span> <span class=\"s1\">&#39;Right&#39;</span><span class=\"p\">:</span>\n",
" <span class=\"n\">agent</span><span class=\"o\">.</span><span class=\"n\">location</span> <span class=\"o\">=</span> <span class=\"n\">loc_B</span>\n",
" <span class=\"n\">agent</span><span class=\"o\">.</span><span class=\"n\">performance</span> <span class=\"o\">-=</span> <span class=\"mi\">1</span>\n",
" <span class=\"k\">elif</span> <span class=\"n\">action</span> <span class=\"o\">==</span> <span class=\"s1\">&#39;Left&#39;</span><span class=\"p\">:</span>\n",
" <span class=\"n\">agent</span><span class=\"o\">.</span><span class=\"n\">location</span> <span class=\"o\">=</span> <span class=\"n\">loc_A</span>\n",
" <span class=\"n\">agent</span><span class=\"o\">.</span><span class=\"n\">performance</span> <span class=\"o\">-=</span> <span class=\"mi\">1</span>\n",
" <span class=\"k\">elif</span> <span class=\"n\">action</span> <span class=\"o\">==</span> <span class=\"s1\">&#39;Suck&#39;</span><span class=\"p\">:</span>\n",
" <span class=\"k\">if</span> <span class=\"bp\">self</span><span class=\"o\">.</span><span class=\"n\">status</span><span class=\"p\">[</span><span class=\"n\">agent</span><span class=\"o\">.</span><span class=\"n\">location</span><span class=\"p\">]</span> <span class=\"o\">==</span> <span class=\"s1\">&#39;Dirty&#39;</span><span class=\"p\">:</span>\n",
" <span class=\"n\">agent</span><span class=\"o\">.</span><span class=\"n\">performance</span> <span class=\"o\">+=</span> <span class=\"mi\">10</span>\n",
" <span class=\"bp\">self</span><span class=\"o\">.</span><span class=\"n\">status</span><span class=\"p\">[</span><span class=\"n\">agent</span><span class=\"o\">.</span><span class=\"n\">location</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"s1\">&#39;Clean&#39;</span>\n",
"\n",
" <span class=\"k\">def</span> <span class=\"nf\">default_location</span><span class=\"p\">(</span><span class=\"bp\">self</span><span class=\"p\">,</span> <span class=\"n\">thing</span><span class=\"p\">):</span>\n",
" <span class=\"sd\">&quot;&quot;&quot;Agents start in either location at random.&quot;&quot;&quot;</span>\n",
" <span class=\"k\">return</span> <span class=\"n\">random</span><span class=\"o\">.</span><span class=\"n\">choice</span><span class=\"p\">([</span><span class=\"n\">loc_A</span><span class=\"p\">,</span> <span class=\"n\">loc_B</span><span class=\"p\">])</span>\n",
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"cell_type": "code",
"execution_count": 3,
"execution_count": 22,
"metadata": {},
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{
"name": "stdout",
"output_type": "stream",
"text": [
"State of the Environment: {(0, 0): 'Dirty', (1, 0): 'Clean'}.\n"
"State of the Environment: {(0, 0): 'Dirty', (1, 0): 'Dirty'}.\n"
]
}
],
Expand All @@ -130,7 +268,7 @@
},
{
"cell_type": "code",
"execution_count": 4,
"execution_count": 23,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -147,7 +285,7 @@
},
{
"cell_type": "code",
"execution_count": 5,
"execution_count": 24,
"metadata": {},
"outputs": [
{
Expand All @@ -174,14 +312,14 @@
},
{
"cell_type": "code",
"execution_count": 6,
"execution_count": 25,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"State of the Environment: {(0, 0): 'Dirty', (1, 0): 'Clean'}.\n",
"State of the Environment: {(0, 0): 'Dirty', (1, 0): 'Dirty'}.\n",
"RandomVacuumAgent is located at (0, 0).\n"
]
}
Expand All @@ -208,7 +346,7 @@
},
{
"cell_type": "code",
"execution_count": 7,
"execution_count": 26,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -234,7 +372,7 @@
},
{
"cell_type": "code",
"execution_count": 8,
"execution_count": 27,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -251,7 +389,7 @@
},
{
"cell_type": "code",
"execution_count": 9,
"execution_count": 28,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -260,7 +398,7 @@
},
{
"cell_type": "code",
"execution_count": 10,
"execution_count": 29,
"metadata": {},
"outputs": [
{
Expand All @@ -280,14 +418,14 @@
},
{
"cell_type": "code",
"execution_count": 11,
"execution_count": 30,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"State of the Environment: {(0, 0): 'Clean', (1, 0): 'Clean'}.\n",
"State of the Environment: {(0, 0): 'Clean', (1, 0): 'Dirty'}.\n",
"TableDrivenVacuumAgent is located at (0, 0).\n"
]
}
Expand All @@ -312,7 +450,7 @@
"\n",
"The schematic diagram shown in **Figure 2.9** of the book will make this more clear:\n",
"\n",
"<img src=\"/files/images/simple_reflex_agent.jpg\">"
"![simple reflex agent](images/simple_reflex_agent.jpg)"
]
},
{
Expand All @@ -324,7 +462,7 @@
},
{
"cell_type": "code",
"execution_count": 12,
"execution_count": 31,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -336,21 +474,36 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"To create our agent, we need two functions: INTERPRET-INPUT function, which generates an abstracted description of the current state from the percerpt and the RULE-MATCH function, which returns the first rule in the set of rules that matches the given state description."
"To create our agent, we need two functions: INTERPRET-INPUT function, which generates an abstracted description of the current state from the percerpt and the RULE-MATCH function, which returns the first rule in the set of rules that matches the given state description. For rules, we will implement a `Rule` class."
]
},
{
"cell_type": "code",
"execution_count": 13,
"execution_count": 32,
"metadata": {},
"outputs": [],
"source": [
"# TODO: Implement these functions for two-dimensional environment\n",
"\n",
"# Rule class\n",
"class Rule:\n",
" def __init__(self, state, action):\n",
" self.__state = state\n",
" self.action = action\n",
" \n",
" def matches(self, state):\n",
" return self.__state == state\n",
"\n",
"# Interpret-input function for the two-state environment\n",
"def interpret_input(percept):\n",
" pass\n",
"def interpret_input(state):\n",
" return state\n",
" \n",
"loc_A = (0, 0)\n",
"loc_B = (1, 0)\n",
"\n",
"rules = None\n",
"# create rules for a two-state Vacuum Environment\n",
"rules = [Rule((loc_A, \"Dirty\"), \"Suck\"), Rule((loc_A, \"Clean\"), \"Right\"),\n",
" Rule((loc_B, \"Dirty\"), \"Suck\"), Rule((loc_B, \"Clean\"), \"Left\")]\n",
"\n",
"# Rule-match function for the two-state environment\n",
"def rule_match(state, rule):\n",
Expand All @@ -359,7 +512,8 @@
" return rule \n",
" \n",
"# Create a simple reflex agent the two-state environment\n",
"simple_reflex_agent = ReflexVacuumAgent()"
"program = SimpleReflexAgentProgram(rules, interpret_input)\n",
"simple_reflex_agent = Agent(program)"
]
},
{
Expand All @@ -371,45 +525,45 @@
},
{
"cell_type": "code",
"execution_count": 14,
"execution_count": 33,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SimpleReflexVacuumAgent is located at (1, 0).\n"
"SimpleReflexAgent is located at (1, 0).\n"
]
}
],
"source": [
"trivial_vacuum_env.add_thing(simple_reflex_agent)\n",
"\n",
"print(\"SimpleReflexVacuumAgent is located at {}.\".format(simple_reflex_agent.location))"
"print(\"SimpleReflexAgent is located at {}.\".format(simple_reflex_agent.location))"
]
},
{
"cell_type": "code",
"execution_count": 15,
"execution_count": 34,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"State of the Environment: {(0, 0): 'Clean', (1, 0): 'Clean'}.\n",
"SimpleReflexVacuumAgent is located at (0, 0).\n"
"SimpleReflexAgent is located at (0, 0).\n"
]
}
],
"source": [
"# Run the environment\n",
"trivial_vacuum_env.step()\n",
"trivial_vacuum_env.run()\n",
"\n",
"# Check the current state of the environment\n",
"print(\"State of the Environment: {}.\".format(trivial_vacuum_env.status))\n",
"\n",
"print(\"SimpleReflexVacuumAgent is located at {}.\".format(simple_reflex_agent.location))"
"print(\"SimpleReflexAgent is located at {}.\".format(simple_reflex_agent.location))"
]
},
{
Expand Down Expand Up @@ -551,7 +705,7 @@
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Expand Down