Sundog Balance
Recovers inside the lighting envelope; fails cleanly at the shadow boundary.
Open workbench ->Alignment Without Sight
Watch the Sundog Alignment Theorem unfold in real time. Each arc marks a different kind of evidence.
The Sundog Project turns indirect signals into usable control: software that doesn't need perfect information to behave intelligently.
Application Rail
Short field notes from confirmed studies, public prototypes, and planned workbenches.
Recovers inside the lighting envelope; fails cleanly at the shadow boundary.
Open workbench ->Guarded local signals survive the near-escape pocket, not the whole cosmos.
Open workbench ->No target coordinates; just detector response, motion, and a closed loop.
Read result ->A noisy pressure field buys more safe progress before failure inside a narrow mapped pocket.
Open workbench ->Roguelike agents acting from compressed perception instead of full sight.
View case ->NPC motion pulled by verbs and needs, not just shortest-path errands.
View case ->Softbody terrain reads through graph signatures, recovery, and strain.
View case ->The animation above is not decoration. It is a map of the idea in three registers: theorem as math, theorem as design method, and theorem as empirical claim. The controlled result remains narrow: photometric mirror alignment without target-position access.
A sundog is useful here because it makes the core move visible: the thing you can use is not always the thing itself. In the field origin, the laser was blocked by the fastener head. In the experiment, the target position is hidden. Sundog begins when occlusion stops being treated as missing data and becomes a readable signal.
The second parhelion gives the scene a frame: source, target, obstruction, projection, and action. As math, Sundog asks whether the projection changes coherently when the agent acts. As design method, it says to instrument that relationship instead of demanding full world state up front.
The upper arc is the dangerous part: it tempts a universal theorem. We keep it conditional. A nonzero relationship between action and signal is not magic; it is a candidate observability channel. The mathematical work is to define that coupling tightly enough that it predicts progress instead of merely sounding profound.
The lower arc turns the origin story into an empirical task. The controller moves a mirrored end-effector and sees detector intensity plus proprioception, not the target coordinates. Its job is to make the reflected beam land where it should by following the signature produced by its own motion.
When the iris closes, the claim becomes measurable. In 30 matched MuJoCo scenes, the photometric controller reached terminal accuracy statistically indistinguishable from the target-aware analytic baseline. The trade was time: indirect feedback converged more slowly. The known failure boundary is tight joint limits.
The outer halo keeps the registers separate. As math, Sundog is a coupling problem. As design method, it is a way to build from partial, indirect signals. As empirical claim, today, it is the photometric mirror-alignment result. The three-body workbench, EyesOnly, Dungeon Gleaner, and Money Bags are application expressions that motivate the next tests.
Most systems do not reveal their truth directly. You infer them from signatures: shadows, feedback, distortions, response curves.
The Sundog Project is a framework for turning those indirect signals into actionable software control. Where conventional approaches demand complete world state, Sundog asks whether the partial signal, the shadow, the torque, the occlusion, already contains enough structure to act.
In the core experiment, a controller aligns a reflected beam without target coordinates, using only sparse photometric feedback. In workbench and product systems, the same pattern informs guarded three-body control under partial local signals, procedural agents acting under occluded state, verb-field NPC behavior, and softbody motion made interpretable through graph signatures.
Occlusion, expense, or design constraints often make full state access impossible. Sundog operates from partial information.
Agents that know less can feel more alive. Sundog enables coherent behavior from compressed state.
Instead of raw simulation noise, Sundog transforms physical traces into legible metrics: alignment, torsion, deformation, recovery.
Demonstrated across operating-envelope workbenches, procedural roguelikes, physical simulation, and softbody terrain systems in AI, games, simulation, and tooling.
A controller aligns a reflected beam without target coordinates, matching oracle baseline accuracy in controlled experiments.
Learn More →A guarded accelerometer-proxy TRACK controller improves survival over passive and naive local baselines inside a tested high-velocity near-escape pocket, while low-velocity and equal-mass cells remain explicit failure boundaries.
Learn More →A shadow-derived cart-pole controller maintains balance inside a mapped lighting and delay envelope, while overhead-light and high-delay cells remain explicit degradation boundaries.
Learn More →Procedural roguelike agents act from compressed perception using stop-conditioned action batches.
Learn More →NPCs in a dungeon-crawler town drift between work, social, and errand spots by following the gradient of their own unmet needs. No scripted schedules, no behavior trees, no goal-oriented planner. Personality is per-archetype weighting on a shared vocabulary of verbs.
Learn More →Softbody terrain system with graph-based telemetry: torsion, deformation, symmetry, and recovery made legible.
Learn More →Same environment. Same task. Different control logic. Observable difference in behavior.
Photometric controller reaches comparable terminal accuracy.
The cost of indirect feedback is time, not accuracy.
Known failure at tight joint limits.
Utility demonstrated across domains.
The Sundog Project is an independent applied research initiative. The defensible scientific claim is narrow: photometric mirror alignment without target-position access in a controlled MuJoCo experiment. The broader applications demonstrate practical utility across procedural systems, simulation, and agent design.
We are continuing to formalize the mathematics, strengthen experimental evidence, and explore new application domains.
Open repository, reproducible experiments, comprehensive documentation, and stress test results.
Independent replication, collaboration on formalization, application-specific studies, and critical review.
Independent applied research project with experimental software lab as secondary identity.