Autonomous agent for task/action planning and execution
Project description
ActionGraph
ActionGraph is a symbolic AI agent for generating action plans based on preconditions and effects. This is loosely based on STRIPS approach (https://en.wikipedia.org/wiki/Stanford_Research_Institute_Problem_Solver). State variables are modeled as nodes; the actions represent edges/transitions from one state to another. Dijikstra's shortest path algorithm (A* but without the heuristic cost estimate) is used to generate a feasible, lowest cost plan.
Source: https://github.com/bharathra/ACTION_GRAPH
Usage:
from action_graph.agent import Agent
from action_graph.action import Action
class Drive(Action):
effects = {"driving": True}
preconditions = {"has_drivers_license": True, "tank_has_gas": True}
class FillGas(Action):
effects = {"tank_has_gas": True}
preconditions = {"has_car": True}
class RentCar(Action):
effects = {"has_car": True}
cost = 100 # dollars
class BuyCar(Action):
effects = {"has_car": True}
preconditions = {}
cost = 10_000 # dollars
if __name__ == "__main__":
world_state = {"has_car": False, "has_drivers_license": True}
goal_state = {"driving": True}
ai = Agent()
actions = [a(ai) for a in Action.__subclasses__()]
ai.load_actions(actions)
print("Initial State:", world_state)
ai.update_state(world_state)
print("Goal State: ", goal_state)
plan = ai.get_plan(goal_state)
# ai.execute_plan(plan)
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file action-graph-1.3.5.tar.gz
.
File metadata
- Download URL: action-graph-1.3.5.tar.gz
- Upload date:
- Size: 8.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.8.10
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 80341d5afc49a204c82e860733002444539fb47568b3c367fe98043bb7778bbe |
|
MD5 | 39af13f02fccef9e2ece0914207d5832 |
|
BLAKE2b-256 | 1fc100827cbc8e5328931241edaa186b38a75894b8e12b08f0864692fac20204 |
File details
Details for the file action_graph-1.3.5-py3-none-any.whl
.
File metadata
- Download URL: action_graph-1.3.5-py3-none-any.whl
- Upload date:
- Size: 9.0 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.8.10
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | b2f32998a75601ca108845dbf4019c64acb3ffff6fa9cc583a0f32e16588d1ee |
|
MD5 | d618300723a6d358a160e8fd9f5106c3 |
|
BLAKE2b-256 | 79001ae916475a29a7fc1da63bbf7e1bb7e0c3108351fd179dc9c92a530188cd |