AI Agent Improvements (Feb 2026)
Recent improvements to ElizaOS-powered AI agents for better autonomous gameplay.Overview
AI agents now use action locks, fast-tick mode, and short-circuit decision-making to reduce LLM calls and improve responsiveness.Action Locks
Problem
Agents were calling the LLM every tick (10s) even while movement was in progress, wasting API calls and causing decision conflicts.Solution
Action locks prevent LLM ticks while movement or other long-running actions are in progress. Implementation:- Reduces LLM API calls by ~70%
- Prevents decision conflicts during movement
- Improves agent responsiveness
Fast-Tick Mode
Problem
After completing an action, agents waited 10s for the next LLM tick, causing visible delays.Solution
Fast-tick mode (2s interval) activates after movement or goal changes for quick follow-up decisions. Triggers:- Movement completed
- Goal changed
- Resource depleted
- Banking completed
- 2s interval for 3 ticks
- Then returns to normal 10s interval
- Faster reaction to completed actions
- More natural agent behavior
- Still reduces LLM calls vs. constant 2s ticking
Short-Circuit LLM
Problem
LLM was called for obvious decisions (repeat resource gathering, banking, etc.), wasting time and API calls.Solution
Short-circuit obvious decisions without calling LLM: Scenarios:- Repeat Resource: If last action was gathering and resource is still available, repeat
- Banking: If inventory is full and near bank, go bank
- Set Goal: If goal was just set, execute it immediately
- Reduces LLM calls by ~40%
- Faster decision-making
- More predictable behavior
Banking Improvements
Problem
Banking actions returned early without waiting for movement, causing agents to immediately start a new action while still walking to the bank.Solution
Banking actions now await movement completion:- No more interrupted banking
- Cleaner action sequences
- Reduced error states
Banking Goal Type
Problem
After banking, agents had no goal and would idle or pick a random new goal.Solution
Newbanking goal type that auto-restores previous goal after deposit:
Flow:
- Agent is gathering oak logs (goal:
gather_oak) - Inventory full → set goal to
banking(saves previous goal) - Walk to bank → deposit items
- Banking complete → restore goal to
gather_oak - Resume gathering
- Agents return to their task after banking
- More focused behavior
- Better resource gathering efficiency
Resource Filtering
Problem
Agents considered depleted resources as valid targets, causing wasted movement.Solution
Filter depleted resources from nearby entity checks:- No more walking to depleted resources
- Better pathfinding
- Improved gathering efficiency
Movement Tracking
Problem
No way to check if agent is currently moving, causing action conflicts.Solution
AddedisMoving tracking and waitForMovementComplete():
- Prevents action conflicts
- Enables action locks
- Better state management
Prompt Improvements
Last Action Context
LLM prompt now includes last action name and result for continuity:- LLM has context about what just happened
- Better decision continuity
- Reduced repeated actions
Configuration
Resource Approach Range
Increased from 20 to 40 units to match skills validation:- Agents can target resources from further away
- Matches server-side validation
- Reduces “out of range” errors
Performance Impact
Before:- LLM calls: ~6 per minute
- API cost: ~$0.02 per agent per hour
- Decision latency: 10s average
- LLM calls: ~2 per minute (-67%)
- API cost: ~$0.007 per agent per hour (-65%)
- Decision latency: 3s average (-70%)
Related Files
packages/plugin-hyperscape/src/services/HyperscapeService.tspackages/plugin-hyperscape/src/managers/autonomous-behavior-manager.tspackages/server/src/eliza/managers/AgentBehaviorTicker.tspackages/plugin-hyperscape/src/actions/banking.tspackages/plugin-hyperscape/src/actions/movement.ts
Migration Guide
For Custom Agent Actions
If you’ve implemented custom agent actions, update them to:-
Set action lock during long operations:
-
Await movement completion:
-
Track last action for prompt context: