Agentic Service Computing (ASC)

• Agentic Service Computing (ASC) is a computational paradigm where autonomous agents, powered by generative AI, mediate market interactions and streamline service orchestration.
• It leverages layered architectures, diverse protocols, and dynamic market structures to enable unscripted natural language negotiations and API-driven transactions.
• ASC reduces communication friction and operational costs, with empirical benchmarks showing improvements in token consumption, cognitive load, and cross-platform efficiency.

Agentic Service Computing (ASC) is a computational paradigm in which autonomous software agents, typically powered by large-scale generative AI, mediate all market interactions and service orchestration. In ASC, consumers delegate intent and preferences to assistant agents, while businesses expose their capabilities through service agents. These entities communicate via unscripted natural language and programmatic APIs, enabling automated discovery, negotiation, transaction execution, and workflow coordination on behalf of their human principals. The ASC framework spans layered architectures, heterogeneous protocol ecosystems (e.g., A2A, MCP), and dynamic market structures, fundamentally reducing communication frictions and transforming traditional service and transaction workflows (Rothschild et al., 21 May 2025).

1. Foundational Definition and Scope

In ASC, assistant agents encapsulate individual user intent, profile, privacy constraints, and budgetary limits, acting as autonomously negotiating and transacting proxies. Service agents represent enterprise capabilities—catalogs, pricing rules, and deliverables—made available through open or proprietary programmatic interfaces. Formally, the agent's core logic is modeled as

$$f: \mathcal{S} \times \mathcal{C} \rightarrow \mathcal{A}$$

where $\mathcal{S}$ denotes agent state (memory, profile, interaction history), $\mathcal{C}$ represents incoming context (utterance embedding, API response, offer), and $\mathcal{A}$ is the action space (e.g., reply, API call, negotiation, booking) (Rothschild et al., 21 May 2025).

Service composition and orchestration are represented as directed workflow graphs $G = (V, E)$, with agent endpoints as vertices and message/API channels as edges, each annotated by reliability and latency. The compounded end-to-end success probability is

$$P_{\text{success}} \approx \prod_{(i \rightarrow j) \in \text{path}} P_i(a_{i \rightarrow j} | s_i, c_i)$$

reflecting uncertainty propagation through agent chains.

2. Layered Architecture and Core Protocols

ASC systems are architected around three primary layers (Rothschild et al., 21 May 2025, Cui et al., 11 Dec 2025):

• Agent Interface Layer: Each agent exposes an NLU endpoint (unscripted language ingestion), a programmatic API (REST/gRPC), and a local planning/decision module (LLM with stateful memory).
• Communication Fabric: Protocol standards facilitating agent discovery, authentication, and message exchange (e.g., AutoGen, MCP, A2A).
• Infrastructure Services: Service registry/discovery (agent-DNS analog), decentralized identity/authentication schemes (PKI, credential-based), secure payment ledgers for micro-transactions, and feedback/reputation stores.

Integration of natural language with API-driven workflows is orchestrated in two phases: interpreting user utterances into intermediate semantics, then translating those into structured API calls for service agents. Decoupled memory—such as Sovereign Memory Pod architectures—further enables stateless composition, persistent data asset management, and low-friction migration across heterogeneous services (Cui et al., 11 Dec 2025).

3. Interaction Modes, Discovery, and Market Structure

Three interaction paradigms are formalized within ASC (Rothschild et al., 21 May 2025):

• Scripted Interactions: Predefined APIs, rigid schemas, high reliability, low flexibility.
• Unscripted Interactions: Natural language negotiation, high expressiveness, increased ambiguity.
• Unrestricted Interactions: Hybridized, free-text negotiation followed by structured API exchange.

The ecosystem bifurcates into agentic walled gardens—closed, vendor-managed platforms with strict access policies—and a web of agents, representing open, protocol-driven networks with universal agent discovery and interoperability. Governance frameworks and technical standards mediate which modes prevail, balancing regulatory demands with innovation imperatives.

4. Economic Implications and Service Optimization

ASC agents, by internalizing preference and context, collapse communication overhead (switching costs per Klemperer’s framework) and facilitate frictionless transactions (Rothschild et al., 21 May 2025). Key economic outcomes include:

• Expanded Consumer Choice: Agents seamlessly traverse hundreds of service endpoints without repeated profile onboarding.
• Dynamic Bundling: Agents and service endpoints collaboratively apply retrieval-augmented generation (RAG) to custom-tailor digital goods, omitting known information or redundant news.
• Micro-transaction Enablement: Automated, agent-mediated payments permit ultra-fine-grained transaction economics (per paragraph, recipe step, API query).

Discovery and advertising transition from human attention capture (ad impressions) to agent-to-agent matching, with sponsored prioritization, agent-level bid-for-position auctions, and persistent feedback serving as the scarce resource.

5. Limitations, Interoperability, and Future Directions

Existing ASC implementations predominantly fall into "siloed agent" stacks (closed ecosystem, non-interoperable) or "end-to-end agents" (screen-scraping, browser simulation) lacking protocol-level compatibility (Rothschild et al., 21 May 2025). Full realization of ASC requires:

• Protocol and Ontology Standardization: Unified message formats, ontologies, security/trust anchors for cross-vendor agent communication.
• Governance Mechanism Design: Dispute resolution, liability assignment, safety and ethical alignment enforcement.
• Market and Incentive Structures: Preference-driven advertising economics, automated clearing for micro-payments, and negotiation protocols supporting multi-party agent workflows.
• Security, Safety, and Alignment: Ensuring agent actions are bounded by human values, resisting collusion and adversarial deviation.

Open issues include the tension between innovation-enabling agent webs and restrictive walled gardens, the need for governance models combining openness with accountability, and development of incentivization mechanisms that avoid concentration and lock-in.

6. Empirical Performance and Operational Metrics

Simulation and benchmarked deployment of ASC paradigms, such as SoDA-enabled systems, demonstrate:

• Token Consumption: 27–35% reduction in complex orchestration and service migration versus baseline RAG agents (Cui et al., 11 Dec 2025).
• Cognitive Load: 72–88% reduction compared to manual operation, accompanied by significant information SNR improvement.
• Cross-Platform Migration Efficiency: Session startup times halved, with a drop from 25.21 s (manual) to 11.38 s (SoDA).
• Privacy-Utility Tradeoff: Over 97% high-risk transaction protection at full service availability, adjustable via strictness parameter thresholds.

These results confirm the practical viability of the ASC memory model, risk-governed execution, and agent-AI integration principles.

7. Research Frontiers and Technical Standardization

Priority research involves developing protocol stacks and meta-standards for agent interoperability, context sharing, and secure intent handling (e.g., UPDL for profile exchange) (Cui et al., 11 Dec 2025). This extends to decentralized reputation/attestation, longitudinal human-centred studies to establish usability, and reinforcement learning-driven privacy-utility tradeoff optimization.

Technically, the future of ASC will be shaped by agent protocol standardization, robust governance, incentive-compatible economic mechanism design, and comprehensive safety/alignment frameworks. The path chosen—walled garden versus open web—will be the determinant of whether ASC catalyzes democratized economic access or entrenched concentration and platform dependency. ASC thus represents the inflection point for generative AI-driven service architectures (Rothschild et al., 21 May 2025).