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Added air_cargo to planning.ipynb (aimacode#835)
* Added air_cargo to planning.ipynb * Some style issues
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‎README.md

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@@ -108,7 +108,7 @@ Here is a table of algorithms, the figure, name of the algorithm in the book and
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| 9.3 | FOL-FC-Ask | `fol_fc_ask` | [`logic.py`][logic] | Done | |
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| 9.6 | FOL-BC-Ask | `fol_bc_ask` | [`logic.py`][logic] | Done | |
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| 9.8 | Append | | | | |
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| 10.1 | Air-Cargo-problem | `air_cargo` | [`planning.py`][planning] | Done | |
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| 10.1 | Air-Cargo-problem | `air_cargo` | [`planning.py`][planning] | Done | Included |
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| 10.2 | Spare-Tire-Problem | `spare_tire` | [`planning.py`][planning] | Done | |
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| 10.3 | Three-Block-Tower | `three_block_tower` | [`planning.py`][planning] | Done | |
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| 10.7 | Cake-Problem | `have_cake_and_eat_cake_too` | [`planning.py`][planning] | Done | |

‎planning.ipynb

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@@ -23,9 +23,7 @@
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {
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"collapsed": false
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"from planning import *"
@@ -51,9 +49,7 @@
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {
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"collapsed": false
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"%psource Action"
@@ -83,9 +79,7 @@
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {
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"collapsed": false
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"%psource PDDL"
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {
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"collapsed": false
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"from utils import *\n",
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {
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"collapsed": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"knowledge_base.extend([\n",
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {
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"collapsed": false
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},
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"metadata": {},
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"outputs": [
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{
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"data": {
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {
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"collapsed": false
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"#Sibiu to Bucharest\n",
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{
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {
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"collapsed": true
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"metadata": {},
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"outputs": [],
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"source": [
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"#Drive\n",
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{
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"cell_type": "code",
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"execution_count": 9,
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"metadata": {
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"collapsed": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"def goal_test(kb):\n",
@@ -303,31 +285,119 @@
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{
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"cell_type": "code",
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"execution_count": 10,
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"metadata": {
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"collapsed": false
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"prob = PDDL(knowledge_base, [fly_s_b, fly_b_s, fly_s_c, fly_c_s, fly_b_c, fly_c_b, drive], goal_test)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Air Cargo Problem:"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Air Cargo problem involves loading and unloading of cargo and flying it from place to place. The problem can be with defined with three actions: Load, Unload and Fly. Let us now define an object of `air_cargo` problem:"
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]
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},
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"execution_count": 15,
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"metadata": {},
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"outputs": [],
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"source": []
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"source": [
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"airCargo = air_cargo()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Now, before taking any actions, we will check the `airCargo` if it has completed the goal it is required to do:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"False\n"
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]
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}
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],
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"source": [
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"print(airCargo.goal_test())"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"As we can see, it hasn't completed the goal. Now, we define the sequence of actions that it should take in order to achieve\n",
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"the goal. Then the `airCargo` acts on each of them."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 17,
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"metadata": {},
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"outputs": [],
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"source": [
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"solution = [expr(\"Load(C1 , P1, SFO)\"),\n",
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" expr(\"Fly(P1, SFO, JFK)\"),\n",
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" expr(\"Unload(C1, P1, JFK)\"),\n",
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" expr(\"Load(C2, P2, JFK)\"),\n",
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" expr(\"Fly(P2, JFK, SFO)\"),\n",
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" expr(\"Unload (C2, P2, SFO)\")] \n",
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"\n",
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"for action in solution:\n",
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" airCargo.act(action)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"As the `airCargo` has taken all the steps it needed in order to achieve the goal, we can now check if it has acheived its goal:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 18,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"True"
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]
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},
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"execution_count": 18,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"airCargo.goal_test()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"metadata": {},
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"outputs": [],
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"source": []
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"source": [
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"It has now achieved its goal."
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]
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}
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],
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"metadata": {
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.4.3"
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"version": "3.6.4"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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"nbformat_minor": 1
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}

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