Pragnay/randomagents

[mpragnay]

Spawning logic added with a random number of agents and randomized dimensions
Integrated with the 2.0 goal sampling for initial goals
Collision and off-road checks during spawns

[greptile-apps]

Greptile Overview

Greptile Summary

This PR implements random agent spawning with configurable dimensions and collision-free placement. Agents are spawned with randomized vehicle dimensions (width, length, height) on drivable lanes, with rejection sampling to prevent collisions and offroad placements. Initial goals are sampled using the 2.0 goal sampling logic.

Key Changes:

• Added random_agents initialization mode with configurable agent counts per environment (min_agents_per_env, max_agents_per_env)
• Implemented collision and offroad checking during spawn via check_spawn_collision and check_spawn_offroad functions
• Added randomized vehicle dimensions via AgentSpawnSettings struct with configurable bounds
• Removed max_controlled_agents parameter in favor of new spawning system
• Integrated 2.0 goal sampling logic for initial goal generation

Critical Issues Found:

• Runtime error in drive.py:279-280: undefined attributes self.min_spawn_agents and self.max_spawn_agents (should be min_agents_per_env and max_agents_per_env)
• Logic error in drive.h:3484: incorrect cosine calculation using atan2f instead of vector magnitude
• Logic error in drive.h:1304-1322: spawn position always updated even when all rejection attempts fail
• Logic error in drive.h:2144-2146: respawn_agent respawns all agents instead of just the individual agent in random mode

Confidence Score: 1/5

• This PR will cause immediate runtime failures and has critical logic errors
• The undefined attribute references in drive.py will cause AttributeError on initialization. Additionally, critical logic bugs in spawn validation, respawn behavior, and goal sampling math will cause incorrect simulation behavior if the runtime errors are fixed
• Pay close attention to pufferlib/ocean/drive/drive.py (runtime errors) and pufferlib/ocean/drive/drive.h (logic errors in spawn/respawn/goal sampling)

Important Files Changed

Filename	Overview
pufferlib/ocean/drive/binding.c	added random agent distribution logic across environments, removed max_controlled_agents parameter
pufferlib/ocean/drive/drive.c	added debug config logging and random agent count support in demo mode
pufferlib/ocean/drive/drive.h	major spawning logic implementation with collision/offroad checks, but contains critical bugs in respawn logic, spawn validation, and goal sampling math
pufferlib/ocean/drive/drive.py	added Python bindings for random spawning parameters, but has undefined attribute references that will cause runtime errors
pufferlib/ocean/env_config.h	added config parsing for spawn dimension parameters and init_mode string parsing

Sequence Diagram

sequenceDiagram
    participant Python as Drive.py
    participant Binding as binding.c
    participant Core as drive.h
    
    Python->>Binding: shared() with random_agents mode
    Binding->>Binding: Distribute agents across envs
    Binding-->>Python: agent_offsets, map_ids, env_count
    
    Python->>Binding: env_init() for each env
    Binding->>Core: Initialize Drive struct
    Core->>Core: load_map_binary()
    Core->>Core: set_active_agents()
    Core->>Core: spawn_agents_with_counts()
    
    loop For each agent
        Core->>Core: spawn_agent()
        Core->>Core: Random vehicle dimensions
        
        loop Rejection sampling (MAX_SPAWN_ATTEMPTS)
            Core->>Core: get_random_point_on_lane()
            Core->>Core: check_spawn_collision()
            Core->>Core: check_spawn_offroad()
            alt Valid spawn
                Core->>Core: break
            else Invalid
                Core->>Core: continue
            end
        end
        
        Core->>Core: Update agent position & state
    end
    
    Core->>Core: init_goal_positions()
    Core->>Core: sample_new_goal() for each agent
    Core-->>Python: Environment ready

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[greptile-apps]

_{9 files reviewed, 6 comments}

_{Edit Code Review Agent Settings | Greptile}

[greptile-apps]

incorrect cosine calculation - mod_heading uses atan2f which returns an angle, not a magnitude

the cosine is already computed via the dot product formula: cos(theta) = dot / (|v1| * |v2|), where |heading| should be the magnitude (which is 1.0 for normalized heading vectors), not atan2f

Suggested change

	float mod_heading = atan2f(agent->heading_y, agent->heading_x);
	float cos_theta = dot/(mod_to_pt * mod_heading);
	float mod_heading = sqrtf(agent->heading_x * agent->heading_x + agent->heading_y * agent->heading_y);
	float cos_theta = dot/(mod_to_pt * mod_heading);

[Copilot]

Pull request overview

This PR adds a new random_agents initialization mode to the Ocean Drive environment, enabling randomized per-environment agent counts and randomized vehicle dimensions/poses during spawning, with additional spawn-time collision/off-road rejection and integration with goal sampling.

Changes:

• Extend INI/env config and Python/C bindings to support random_agents mode and spawn dimension parameters.
• Implement random agent spawning logic in the C core, including collision/off-road checks and goal initialization behavior.
• Update demo/visualization entrypoints and default drive.ini settings to exercise the new mode.

Reviewed changes

Copilot reviewed 9 out of 9 changed files in this pull request and generated 13 comments.

Show a summary per file

File	Description
pufferlib/ocean/env_config.h	Adds new spawn/agent-count config fields and parses init_mode strings.
pufferlib/ocean/drive/visualize.c	Wires spawn settings into visualization env init; randomizes agent counts in random mode.
pufferlib/ocean/drive/error.h	Extends error types and adjusts error string formatting.
pufferlib/ocean/drive/drive.py	Adds Python-side config for random agent counts/dimensions and passes through to bindings.
pufferlib/ocean/drive/drive.h	Implements spawn rejection sampling, off-road checks, random init mode wiring, and goal sampling adjustments.
pufferlib/ocean/drive/drive.c	Updates demo to use spawn settings and random agent counts; changes default weights/map.
pufferlib/ocean/drive/datatypes.h	Adds free_agents helper to free an array of agents safely.
pufferlib/ocean/drive/binding.c	Adds random agent-count partitioning in shared() and passes spawn settings into env init.
pufferlib/config/ocean/drive.ini	Updates defaults to enable random_agents and sets spawn/agent-count parameters.

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[Copilot]

Pull request overview

Copilot reviewed 10 out of 10 changed files in this pull request and generated 10 comments.

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[Copilot]

spawn_height is currently hardcoded to 1.5f, so the configured env->spawn_settings.h is ignored even though it’s parsed and passed through config/bindings. Use the configured spawn height (and keep the z-centering adjustment) so spawns match the INI/Python parameters.

Suggested change

	float spawn_height = 1.5f; // Design Choice: Doesn't matter as we don't have flying cars in 2026
	float spawn_height = spawn_settings.h;

[Copilot]

load_weights("best_policy_with_reward_conditioning.bin") appears to reference a file that isn’t in the repo and also drops the resources/drive/ prefix used elsewhere. This breaks the demo by default unless the artifact is committed and the path is corrected.

[Copilot]

The upper bound computation for count = min_agents_per_env + rand() % (upper - min_agents_per_env + 1) can yield upper < min_agents_per_env for infeasible combinations of remaining, min_agents_per_env, and max_agents_per_env (e.g. remaining=9, min=5, max=6), leading to modulo-by-zero/UB. Add a feasibility check and a fallback strategy (e.g. error out, relax the min for the final env, or adjust prior counts) before computing the modulo range.

Suggested change

	count = min_agents_per_env + rand() % (upper - min_agents_per_env + 1);
	if (upper < min_agents_per_env) {
	/* Infeasible to satisfy min_agents_per_env for all envs with remaining agents.
	* Fall back by relaxing the minimum for this env: fill up to max_agents_per_env
	* (or all remaining if fewer). This avoids a zero/negative modulo range.
	*/
	count = remaining > max_agents_per_env ? max_agents_per_env : remaining;
	} else {
	count = min_agents_per_env + rand() % (upper - min_agents_per_env + 1);
	}