Hybrid-Wumpus-Agent.md

HYBRID-WUMPUS-AGENT

AIMA3e

function HYBRID-WUMPUS-AGENT(percept) returns an action
 inputs: percept, a list, [stench, breeze, glitter, bump, scream]
 persistent: KB, a knowledge base, initially the atemporal "wumpus physics"
      t, a counter, initially 0, indicating time
      plan, an action sequence, initially empty

 TELL(KB, MAKE-PERCEPT-SENTENCE(percept, t))
 TELL the KB the temporal "physics" sentences for time t
 safe ← {[x, y] : ASK(KB, OK^t_x,y) = true}
 if ASK(KB, Glitter^t) = true then
   plan ← [Grab] + PLAN-ROUTE(current, {[1,1]}, safe) + [Climb]
 if plan is empty then
   unvisited ← {[x, y] : ASK(KB, L^t'_x,y) = false for all t' ≤ t}
   plan ← PLAN-ROUTE(current, unvisited ∩ safe, safe)
 if plan is empty and ASK(KB, HaveArrow^t) = true then
   possible_wumpus ← {[x, y] : ASK(KB, ¬W_x,y) = false}
   plan ← PLAN-SHOT(current, possible_wumpus, safe)
 if plan is empty then //no choice but to take a risk
   not_unsafe ← {[x, y] : ASK(KB, ¬OK^t_x,y) = false}
   plan ← PLAN-ROUTE(current, unvisited ∩ not_unsafe, safe)
 if plan is empty then
   plan ← PLAN-ROUTE(current, {[1,1]}, safe) + [Climb]
 action ← POP(plan)
 TELL(KB, MAKE-ACTION-SENTENCE(action, t))
 t ← t + 1
 return action

---

function PLAN-ROUTE(current, goals, allowed) returns an action sequence
 inputs: current, the agent's current position
     goals, a set of squares; try to plan a route to one of them
     allowed, a set of squares that can form part of the route

 problem ← ROUTE-PROBLEM(current, goals, allowed)
 return A*-GRAPH-SEARCH(problem)

Figure ?? A hybrid agent program for the wumpus world. It uses a propositional knowledge base to infer the state of the world, and a combination of problem-solving search and domain-specific code to decide what actions to take.