arXiv subjects

Anushka Sharma

Publications and source records attributed to Anushka Sharma.

5 recordsLinked to original sources

arXiv2026

Genesis: An Empirical Platform for Studying Open-Ended Evolution Without Fitness Functions

Biological evolution sustains complex dynamics without any fitness function, yet virtually all evolutionary algorithms depend on one. Genesis is an open-source platform designed to test, empirically, what an artificial system needs to sustain evolutionary dynamics after complete fitness removal. Evolution in Genesis is governed by physical constraints, relational dominance, and adaptive regulation - no scalar fitness, no designer-specified objectives. Across experiments totalling over one million evolutionary generations, Genesis has: (i) shown that constraint-driven selection can sustain evolutionary activity after complete fitness removal (7/12 runs; Wilson 95% CI [30.2%, 82.5%]; p<0.01, Cohen's d=1.47 vs. baselines); (ii) produced a sham-controlled negative result demonstrating that niche construction alone does not break the complexity plateau; and (iii) provided preliminary evidence that speciation-protected niche construction initiates structural diversification that unprotected secretion cannot. These findings establish empirical boundaries for fitness-free evolution and open a new direction: meta-evolution of physics, in which the laws governing an evolutionary system are themselves evolved.

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arXiv2026

Evolving Self-Organising Agents Without Fitness: Three Falsifiable Experiments from Constraint-Driven Selection to Developmental Encoding

Can evolutionary dynamics characteristic of biological development arise without a designer-specified fitness function? We present Genesis, a platform in which agents inhabit a Gray-Scott reaction-diffusion substrate and evolve under physical constraints alone. Three successive experimental cycles, each testing one falsifiable hypothesis, show: (1) constraint-driven selection sustains evolutionary activity after complete fitness removal but reaches a hard phenotypic complexity ceiling; (2) agent-mediated niche construction via chemical secretion is real but causally insufficient to break that ceiling; and (3) replacing the fixed-alphabet genome with a Compositional Pattern Producing Network (CPPN) indirect encoding, protected by NEAT-style speciation, produces the first evidence of progressive structural complexification in a fitness-free system. Null results are treated as precise, informative answers rather than failures, yielding reusable diagnostic tools and a sham-control protocol applicable to any open-ended evolution evaluation pipeline.

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arXiv2025

Linear State Estimation in Presence of Bounded Uncertainties: A Comparative Analysis

A variety of algorithms have been proposed to address the power system state estimation problem in the presence of uncertainties in the data. However, less emphasis has been given to handling perturbations in the model. In the context of linear state estimation (LSE), which is the focus of this paper, perturbations in the model come from variations in the line parameters. Since the actual values of the line parameters can be different from the values stored in a power utility's database, we investigate three approaches in this paper to estimate the states in the presence of bounded uncertainties in the data and the model. The first approach is based on interval arithmetic, the second is based on convex optimization, and the third is based on generalized linear fractional programming. The three algorithms are applied to multiple IEEE test systems and compared in terms of their speed and accuracy. The results indicate that the first two algorithms are extremely fast and give expected results, while the third suffers from scalability issues and is unsuitable for LSE.

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arXiv2025

A Practical Approach Towards Inertia Estimation Using Ambient Synchrophasor Data

Real-time tracking of inertia is important because it reflects the power system's ability to withstand contingencies and maintain frequency security. This paper proposes a practical approach to estimate inertia using ambient phasor measurement unit (PMU) data and a partitioned form of the swing equation. The approach accounts for (bounded) uncertainties in network parameters and PMU measurements, enabling precise estimation of inertia and damping constants, as well as mechanical power inputs. Instead of assuming constant mechanical power input throughout, the approach leverages knowledge of power system operations to determine intervals when it is actually constant to maintain estimation consistency. Simulation results on the IEEE 14-bus system and IEEE 39 bus system integrated with renewable energy sources affirm the method's accuracy and applicability.

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arXiv2024

Comparative Analysis of Information Theoretic and Statistical Methods for Line Parameter Estimation

Recent studies indicate that the noise characteristics of phasor measurement units (PMUs) can be more accurately described by non-Gaussian distributions. Consequently, estimation techniques based on Gaussian noise assumptions may produce poor results with PMU data. This paper considers the PMU based line parameter estimation (LPE) problem, and investigates the performance of four state-of-the-art techniques in solving this problem in presence of non-Gaussian measurement noise. The rigorous comparative analysis highlights the merits and demerits of each technique w.r.t. the LPE problem, and identifies conditions under which they are expected to give good results.

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