docs

lab/docs/index.rst

@@ -28,6 +28,7 @@ Quick Start
    :maxdepth: 2
    :caption: Contents:
 
+   system_overview
    modules/outlet
    modules/population
    modules/experiments

lab/docs/system_overview.rst

@@ -0,0 +1,97 @@
+System Overview
+===============
+
+The simulator organises dynamic pricing and market-making experiments as a
+closed loop with the following stages:
+
+* **Quote** – a policy or agent emits a :class:`lab.outlet.types.Quote`. The
+  quote is normalised and validated by a concrete
+  :class:`lab.outlet.protocols.Mechanism` implementation
+  (posted-price, two-sided, auction).
+* **Arrival** – a :class:`lab.outlet.protocols.ArrivalModel` samples a stream of
+  :class:`lab.outlet.types.Opportunity` objects given the current time,
+  instrument catalogue, and market state.
+* **Execution** – the :class:`lab.outlet.protocols.ExecutionModel` converts an
+  opportunity into a probabilistic fill using the active quote, optional
+  competitor prices, and demand-side context.
+* **Position** – a :class:`lab.outlet.protocols.PositionModel` enforces
+  inventory or position constraints, censors oversized fills, and accrues
+  holding and shortage costs.
+* **Observation & Reward** – the
+  :class:`lab.outlet.protocols.ObservationBuilder` constructs the censored view
+  exposed to the agent, while a :class:`lab.outlet.protocols.Objective`
+  transforms :class:`lab.outlet.types.StepMetrics` into a scalar reward with an
+  optional breakdown per term.
+
+These components are orchestrated by :class:`lab.outlet.platform.Platform`,
+which manages internal hidden state, deterministic seeding, and logging.
+
+Component Matrix
+----------------
+
+===============================  ==============================================
+Layer                            Responsibilities / Examples
+===============================  ==============================================
+Mechanisms                       Quote normalisation, execution semantics
+                                 (`posted_price`, `two_sided`, `auction`).
+Population models                Arrivals (:mod:`lab.population.arrivals`),
+                                 execution probability models
+                                 (:mod:`lab.population.execution`), and
+                                 competitor or market dynamics
+                                 (:mod:`lab.population.competitors`).
+Position management              Inventory limits, replenishment, holding and
+                                 shortage costs (:mod:`lab.outlet.stock`).
+Observation & logging            Censored observations and optional event logs
+                                 (:mod:`lab.outlet.observation`).
+Objectives                       Reward composition utilities
+                                 (:mod:`lab.outlet.objectives`).
+Experiments                      Rollout helpers, baseline policies, off-policy
+                                 evaluation (:mod:`lab.experiments.eval`).
+===============================  ==============================================
+
+Preconfigured Platforms
+-----------------------
+
+Two high-level factories in :mod:`lab.config` wire common combinations of the
+building blocks:
+
+* **Retail dynamic pricing** – posted-price mechanism, session arrivals with
+  contamination, elasticity-based executions, reactive competitor model, and a
+  composite objective that penalises volatility, holding costs, and lost
+  opportunities.
+* **Market making** – two-sided quoting, Hawkes order flow, intensity-based
+  executions, geometric Brownian motion mid-prices, and an objective combining
+  PnL, spread capture, and quadratic inventory risk.
+
+State & Reset Behaviour
+-----------------------
+
+When you call :meth:`lab.outlet.platform.Platform.reset`, the platform resets
+instrument positions, quotes, and hidden state, but component implementations
+may maintain their own internal buffers. For reproducible experiments:
+
+* Reuse freshly instantiated arrival/market models per episode, or add explicit
+  ``reset`` methods if the model keeps history (for example,
+  :class:`lab.population.arrivals.HawkesArrivalModel` maintains an event
+  history, while :class:`lab.population.competitors.ReactiveCompetitorModel`
+  tracks prior competitor quotes).
+* Seed randomness through the factory configuration (``RetailConfig.seed`` or
+  ``MarketMakingConfig.seed``) or pass a seed to ``Platform.reset`` for
+  deterministic rollouts.
+
+Extending the Platform
+----------------------
+
+To support a new domain:
+
+1. Create custom Mechanism/Arrival/Execution/Market/Observation components by
+   implementing the respective protocol in :mod:`lab.outlet.protocols`.
+2. Compose a new objective with
+   :func:`lab.outlet.objectives.factory.make_composite` or write a bespoke
+   :class:`lab.outlet.objectives.base.BaseObjective`.
+3. Wire everything together via :class:`lab.outlet.platform.Platform` directly
+   or expose a helper factory in :mod:`lab.config`.
+
+Use :func:`lab.experiments.rollout` and
+:func:`lab.experiments.compare_policies` to benchmark candidate policies under
+multiple random seeds, collecting per-step logs for analysis or OPE.